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ORCIDTie-Yan Liu
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- affiliation: Microsoft Research Asia, Beijing, China
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2020 – today
- 2025
[j77]Rui Zhang
, Qi Meng, Rongchan Zhu, Yue Wang, Wenlei Shi, Shihua Zhang, Zhi-Ming Ma, Tie-Yan Liu:
Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation. IEEE Trans. Pattern Anal. Mach. Intell. 47(6): 5059-5075 (2025)- [i233]Yingce Xia, Peiran Jin, Shufang Xie, Liang He, Chuan Cao, Renqian Luo, Guoqing Liu, Yue Wang, Zequn Liu, Yuan-Jyue Chen, Zekun Guo, Yeqi Bai, Pan Deng, Yaosen Min, Ziheng Lu, Hongxia Hao, Han Yang, Jielan Li, Chang Liu, Jia Zhang, Jianwei Zhu, Kehan Wu, Wei Zhang, Kaiyuan Gao, Qizhi Pei, Qian Wang, Xixian Liu, Yanting Li, Houtian Zhu, Yeqing Lu, Mingqian Ma, Zun Wang, Tian Xie, Krzysztof Maziarz, Marwin H. S. Segler, Zhao Yang, Zilong Chen, Yu Shi, Shuxin Zheng, Lijun Wu, Chen Hu, Peggy Dai, Tie-Yan Liu, Haiguang Liu, Tao Qin:
NatureLM: Deciphering the Language of Nature for Scientific Discovery. CoRR abs/2502.07527 (2025) - [i232]Haoxiang Guan, Jiyan He, Liyang Fan, Zhenzhen Ren, Shaobin He, Xin Yu, Yuan Chen, Shuxin Zheng, Tie-Yan Liu, Zhen Liu:
Modeling Earth-Scale Human-Like Societies with One Billion Agents. CoRR abs/2506.12078 (2025) - 2024
- [j76]Shuxin Zheng, Jiyan He, Chang Liu, Yu Shi, Ziheng Lu, Weitao Feng, Fusong Ju, Jiaxi Wang, Jianwei Zhu, Yaosen Min, He Zhang, Shidi Tang, Hongxia Hao, Peiran Jin, Chi Chen, Frank Noé, Haiguang Liu, Tie-Yan Liu:
Predicting equilibrium distributions for molecular systems with deep learning. Nat. Mac. Intell. 6(5): 558-567 (2024) - [j75]Shuxin Zheng, Jiyan He, Chang Liu, Yu Shi, Ziheng Lu, Weitao Feng, Fusong Ju, Jiaxi Wang, Jianwei Zhu, Yaosen Min, He Zhang, Shidi Tang, Hongxia Hao, Peiran Jin, Chi Chen, Frank Noé, Haiguang Liu, Tie-Yan Liu:
Author Correction: Predicting equilibrium distributions for molecular systems with deep learning. Nat. Mac. Intell. 6(12): 1626 (2024) - [j74]Xinquan Huang, Wenlei Shi, Xiaotian Gao, Xinran Wei, Jia Zhang, Jiang Bian, Mao Yang, Tie-Yan Liu:
LordNet: An efficient neural network for learning to solve parametric partial differential equations without simulated data. Neural Networks 176: 106354 (2024) - [j73]Xu Tan, Jiawei Chen, Haohe Liu, Jian Cong, Chen Zhang, Yanqing Liu, Xi Wang, Yichong Leng, Yuanhao Yi, Lei He, Sheng Zhao, Tao Qin, Frank K. Soong, Tie-Yan Liu:
NaturalSpeech: End-to-End Text-to-Speech Synthesis With Human-Level Quality. IEEE Trans. Pattern Anal. Mach. Intell. 46(6): 4234-4245 (2024) - [j72]Juntao Li, Xiaobo Liang, Lijun Wu, Yue Wang, Qi Meng, Tao Qin, Min Zhang, Tie-Yan Liu:
Randomness Regularization With Simple Consistency Training for Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 46(8): 5763-5778 (2024) - [j71]Velma K. Lopez, Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O'Dea, Madeline Adee, Turgay Ayer, Jagpreet Chhatwal, Ozden O. Dalgic, Mary A. Ladd, Benjamin P. Linas, Peter P. Mueller, Jade Xiao, Johannes Bracher, Alvaro J. Castro Rivadeneira, Aaron Gerding, Tilmann Gneiting, Yuxin Huang, Dasuni Jayawardena, Abdul H. Kanji, Khoa Le, Anja Mühlemann, Jarad Niemi, Evan L. Ray, Ariane Stark, Yijin Wang, Nutcha Wattanachit, Martha W. Zorn, Sen Pei, Jeffrey Shaman, Teresa K. Yamana, Samuel R. Tarasewicz, Daniel J. Wilson, Sid Baccam, Heidi Gurung, Steve Stage, Brad Suchoski, Lei Gao, Zhiling Gu, Myungjin Kim, Xinyi Li, Guannan Wang, Lily Wang, Yueying Wang, Shan Yu, Lauren Gardner, Sonia Jindal, Maximilian Marshall, Kristen Nixon, Juan Dent, Alison L. Hill, Joshua Kaminsky, Elizabeth C. Lee, Joseph Chadi Lemaitre, Justin Lessler, Claire P. Smith, Shaun Truelove, Matt Kinsey, Luke C. Mullany, Kaitlin Rainwater-Lovett, Lauren Shin, Katharine Tallaksen, Shelby Wilson, Dean Karlen, Lauren Castro, Geoffrey Fairchild, Isaac Michaud, Dave Osthus, Jiang Bian, Wei Cao, Zhifeng Gao, Juan Lavista Ferres, Chaozhuo Li, Tie-Yan Liu, Xing Xie, Shun Zhang, Shun Zheng, Matteo Chinazzi, Jessica T. Davis, Kunpeng Mu, Ana L. Pastore y Piontti, Alessandro Vespignani, Xinyue Xiong, Robert Walraven, Jinghui Chen, Quanquan Gu, Lingxiao Wang, Pan Xu, Weitong Zhang, Difan Zou, Graham Casey Gibson, Daniel Sheldon, Ajitesh Srivastava, Aniruddha Adiga, Benjamin Hurt, Gursharn Kaur, Bryan Lewis, Madhav V. Marathe, Akhil Sai Peddireddy, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Lijing Wang, Pragati V. Prasad, Jo W. Walker, Alexander E. Webber, Rachel B. Slayton, Matthew Biggerstaff, Nicholas G. Reich, Michael A. Johansson:
Challenges of COVID-19 Case Forecasting in the US, 2020-2021. PLoS Comput. Biol. 20(5): 1011200 (2024) - [j70]Yang Liu, Chang Xu, Min Hou, Weiqing Liu, Jiang Bian, Qi Liu, Tie-Yan Liu:
Digger-Guider: High-Frequency Factor Extraction for Stock Trend Prediction. IEEE Trans. Knowl. Data Eng. 36(12): 7973-7985 (2024) - [c306]Xu Tan, Tao Qin, Jiang Bian, Tie-Yan Liu, Yoshua Bengio:
Regeneration Learning: A Learning Paradigm for Data Generation. AAAI 2024: 22614-22622 - [c305]Yunyang Li, Yusong Wang, Lin Huang, Han Yang, Xinran Wei, Jia Zhang, Tong Wang, Zun Wang, Bin Shao, Tie-Yan Liu:
Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation. ICLR 2024 - [c304]Tianlang Chen, Shengjie Luo, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang:
GeoMFormer: A General Architecture for Geometric Molecular Representation Learning. ICML 2024 - [c303]He Zhang, Chang Liu, Zun Wang, Xinran Wei, Siyuan Liu, Nanning Zheng, Bin Shao, Tie-Yan Liu:
Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction. ICML 2024 - [c302]Ang Lv, Xu Tan, Tao Qin, Tie-Yan Liu, Rui Yan:
Re-creation of Creations: A New Paradigm for Lyric-to-Melody Generation. IJCAI 2024: 7708-7716 - [c301]Bohan Wang, Yushun Zhang, Huishuai Zhang, Qi Meng, Ruoyu Sun, Zhi-Ming Ma, Tie-Yan Liu, Zhi-Quan Luo, Wei Chen:
Provable Adaptivity of Adam under Non-uniform Smoothness. KDD 2024: 2960-2969 - [c300]Shengjie Luo, Yixian Xu, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang:
Bridging Geometric States via Geometric Diffusion Bridge. NeurIPS 2024 - [c299]Yuxuan Ren, Dihan Zheng, Chang Liu, Peiran Jin, Yu Shi, Lin Huang, Jiyan He, Shengjie Luo, Tao Qin, Tie-Yan Liu:
Physical Consistency Bridges Heterogeneous Data in Molecular Multi-Task Learning. NeurIPS 2024 - [i231]He Zhang, Chang Liu, Zun Wang, Xinran Wei, Siyuan Liu, Nanning Zheng, Bin Shao, Tie-Yan Liu:
Self-Consistency Training for Hamiltonian Prediction. CoRR abs/2403.09560 (2024) - [i230]Tianlang Chen, Shengjie Luo, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang:
GeoMFormer: A General Architecture for Geometric Molecular Representation Learning. CoRR abs/2406.16853 (2024) - [i229]Huayan Zhang, Ruibin Bai, Tie-Yan Liu, Jiawei Li, Bingchen Lin, Jianfeng Ren:
Pattern based learning and optimisation through pricing for bin packing problem. CoRR abs/2409.04456 (2024) - [i228]Yuxuan Ren, Dihan Zheng, Chang Liu, Peiran Jin, Yu Shi, Lin Huang, Jiyan He, Shengjie Luo, Tao Qin, Tie-Yan Liu:
Physical Consistency Bridges Heterogeneous Data in Molecular Multi-Task Learning. CoRR abs/2410.10118 (2024) - [i227]Liang He, Peiran Jin, Yaosen Min, Shufang Xie, Lijun Wu, Tao Qin, Xiaozhuan Liang, Kaiyuan Gao, Yuliang Jiang, Tie-Yan Liu:
SFM-Protein: Integrative Co-evolutionary Pre-training for Advanced Protein Sequence Representation. CoRR abs/2410.24022 (2024) - [i226]Shengjie Luo, Yixian Xu, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang:
Bridging Geometric States via Geometric Diffusion Bridge. CoRR abs/2410.24220 (2024) - 2023
- [j69]Zimeng Li, Shichao Zhu, Bin Shao, Xiangxiang Zeng, Tong Wang, Tie-Yan Liu:
DSN-DDI: an accurate and generalized framework for drug-drug interaction prediction by dual-view representation learning. Briefings Bioinform. 24(1) (2023) - [j68]Jiacheng Lin, Lijun Wu, Jinhua Zhu, Xiaobo Liang, Yingce Xia, Shufang Xie, Tao Qin, Tie-Yan Liu:
R2-DDI: relation-aware feature refinement for drug-drug interaction prediction. Briefings Bioinform. 24(1) (2023) - [j67]Qizhi Pei, Lijun Wu, Jinhua Zhu, Yingce Xia, Shufang Xie, Tao Qin, Haiguang Liu, Tie-Yan Liu, Rui Yan:
Breaking the barriers of data scarcity in drug-target affinity prediction. Briefings Bioinform. 24(6) (2023) - [j66]Mingqing Xiao, Shuxin Zheng, Chang Liu, Zhouchen Lin, Tie-Yan Liu:
Invertible Rescaling Network and Its Extensions. Int. J. Comput. Vis. 131(1): 134-159 (2023) - [j65]Shiqi Gong, Qi Meng, Yue Wang, Lijun Wu, Wei Chen, Zhiming Ma, Tie-Yan Liu:
Incorporating NODE with pre-trained neural differential operator for learning dynamics. Neurocomputing 528: 48-58 (2023) - [j64]Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Anima Anandkumar, Karianne Bergen, Carla P. Gomes, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie-Yan Liu, Arjun Manrai, Debora S. Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Tang, Petar Velickovic, Max Welling, Linfeng Zhang, Connor W. Coley, Yoshua Bengio, Marinka Zitnik:
Scientific discovery in the age of artificial intelligence. Nat. 620(7972): 47-60 (2023) - [j63]Jinhua Zhu, Yingce Xia, Lijun Wu, Jiajun Deng, Wengang Zhou, Tao Qin, Tie-Yan Liu, Houqiang Li:
Masked Contrastive Representation Learning for Reinforcement Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 3421-3433 (2023) - [j62]Yisheng Xiao, Lijun Wu, Junliang Guo, Juntao Li, Min Zhang, Tao Qin, Tie-Yan Liu:
A Survey on Non-Autoregressive Generation for Neural Machine Translation and Beyond. IEEE Trans. Pattern Anal. Mach. Intell. 45(10): 11407-11427 (2023) - [j61]Da Yu, Gautam Kamath, Janardhan Kulkarni, Tie-Yan Liu, Jian Yin, Huishuai Zhang:
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent. Trans. Mach. Learn. Res. 2023 (2023) - [c298]Shiqi Gong, Peiyan Hu, Qi Meng, Yue Wang, Rongchan Zhu, Bingguang Chen, Zhiming Ma, Hao Ni, Tie-Yan Liu:
Deep Latent Regularity Network for Modeling Stochastic Partial Differential Equations. AAAI 2023: 7740-7747 - [c297]Yichong Leng, Xu Tan, Wenjie Liu, Kaitao Song, Rui Wang, Xiang-Yang Li, Tao Qin, Edward Lin, Tie-Yan Liu:
SoftCorrect: Error Correction with Soft Detection for Automatic Speech Recognition. AAAI 2023: 13034-13042 - [c296]Yisheng Xiao, Ruiyang Xu, Lijun Wu, Juntao Li, Tao Qin, Tie-Yan Liu, Min Zhang:
AMOM: Adaptive Masking over Masking for Conditional Masked Language Model. AAAI 2023: 13789-13797 - [c295]Zequn Liu, Wei Zhang, Yingce Xia, Lijun Wu, Shufang Xie, Tao Qin, Ming Zhang, Tie-Yan Liu:
MolXPT: Wrapping Molecules with Text for Generative Pre-training. ACL (2) 2023: 1606-1616 - [c294]Zixin Zeng, Rui Wang, Yichong Leng, Junliang Guo, Shufang Xie, Xu Tan, Tao Qin, Tie-Yan Liu:
Extract and Attend: Improving Entity Translation in Neural Machine Translation. ACL (Findings) 2023: 1697-1710 - [c293]Di He, Shanda Li, Wenlei Shi, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu:
Learning Physics-Informed Neural Networks without Stacked Back-propagation. AISTATS 2023: 3034-3047 - [c292]Zijie Geng, Shufang Xie, Yingce Xia, Lijun Wu, Tao Qin, Jie Wang, Yongdong Zhang, Feng Wu, Tie-Yan Liu:
De Novo Molecular Generation via Connection-aware Motif Mining. ICLR 2023 - [c291]Shengjie Luo, Tianlang Chen, Yixian Xu, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He:
One Transformer Can Understand Both 2D & 3D Molecular Data. ICLR 2023 - [c290]Jinhua Zhu, Yue Wang, Lijun Wu, Tao Qin, Wengang Zhou, Tie-Yan Liu, Houqiang Li:
Making Better Decision by Directly Planning in Continuous Control. ICLR 2023 - [c289]Jinhua Zhu, Kehan Wu, Bohan Wang, Yingce Xia, Shufang Xie, Qi Meng, Lijun Wu, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu:
𝒪-GNN: incorporating ring priors into molecular modeling. ICLR 2023 - [c288]Xinquan Huang, Wenlei Shi, Qi Meng, Yue Wang, Xiaotian Gao, Jia Zhang, Tie-Yan Liu:
NeuralStagger: Accelerating Physics-constrained Neural PDE Solver with Spatial-temporal Decomposition. ICML 2023: 13993-14006 - [c287]Guoqing Liu, Di Xue, Shufang Xie, Yingce Xia, Austin Tripp, Krzysztof Maziarz, Marwin H. S. Segler, Tao Qin, Zongzhang Zhang, Tie-Yan Liu:
Retrosynthetic Planning with Dual Value Networks. ICML 2023: 22266-22276 - [c286]Kaiyuan Gao, Lijun Wu, Jinhua Zhu, Tianbo Peng, Yingce Xia, Liang He, Shufang Xie, Tao Qin, Haiguang Liu, Kun He, Tie-Yan Liu:
Pre-training Antibody Language Models for Antigen-Specific Computational Antibody Design. KDD 2023: 506-517 - [c285]Hangting Ye, Zhining Liu, Wei Cao, Amir M. Amiri, Jiang Bian, Yi Chang, Jon D. Lurie, Jim Weinstein, Tie-Yan Liu:
Web-based Long-term Spine Treatment Outcome Forecasting. KDD 2023: 3082-3092 - [c284]Jinhua Zhu, Yingce Xia, Lijun Wu, Shufang Xie, Wengang Zhou, Tao Qin, Houqiang Li, Tie-Yan Liu:
Dual-view Molecular Pre-training. KDD 2023: 3615-3627 - [c283]Yuchen Fang, Zhenggang Tang, Kan Ren, Weiqing Liu, Li Zhao, Jiang Bian, Dongsheng Li, Weinan Zhang, Yong Yu, Tie-Yan Liu:
Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance. KDD 2023: 4003-4012 - [c282]Qizhi Pei, Kaiyuan Gao, Lijun Wu, Jinhua Zhu, Yingce Xia, Shufang Xie, Tao Qin, Kun He, Tie-Yan Liu, Rui Yan:
FABind: Fast and Accurate Protein-Ligand Binding. NeurIPS 2023 - [c281]Yusong Wang, Shaoning Li, Tong Wang, Bin Shao, Nanning Zheng, Tie-Yan Liu:
Geometric Transformer with Interatomic Positional Encoding. NeurIPS 2023 - [i225]Xu Tan, Tao Qin, Jiang Bian, Tie-Yan Liu, Yoshua Bengio:
Regeneration Learning: A Learning Paradigm for Data Generation. CoRR abs/2301.08846 (2023) - [i224]Guoqing Liu, Di Xue, Shufang Xie, Yingce Xia, Austin Tripp, Krzysztof Maziarz, Marwin H. S. Segler, Tao Qin, Zongzhang Zhang, Tie-Yan Liu:
Retrosynthetic Planning with Dual Value Networks. CoRR abs/2301.13755 (2023) - [i223]Zijie Geng, Shufang Xie, Yingce Xia, Lijun Wu, Tao Qin, Jie Wang, Yongdong Zhang, Feng Wu, Tie-Yan Liu:
De Novo Molecular Generation via Connection-aware Motif Mining. CoRR abs/2302.01129 (2023) - [i222]Rui Zhang, Qi Meng, Rongchan Zhu, Yue Wang, Wenlei Shi, Shihua Zhang, Zhi-Ming Ma, Tie-Yan Liu:
Monte Carlo Neural Operator for Learning PDEs via Probabilistic Representation. CoRR abs/2302.05104 (2023) - [i221]Xinquan Huang, Wenlei Shi, Qi Meng, Yue Wang, Xiaotian Gao, Jia Zhang, Tie-Yan Liu:
NeuralStagger: accelerating physics-constrained neural PDE solver with spatial-temporal decomposition. CoRR abs/2302.10255 (2023) - [i220]Zequn Liu, Wei Zhang, Yingce Xia, Lijun Wu, Shufang Xie, Tao Qin, Ming Zhang, Tie-Yan Liu:
MolXPT: Wrapping Molecules with Text for Generative Pre-training. CoRR abs/2305.10688 (2023) - [i219]Zixin Zeng, Rui Wang, Yichong Leng, Junliang Guo, Xu Tan, Tao Qin, Tie-Yan Liu:
Extract and Attend: Improving Entity Translation in Neural Machine Translation. CoRR abs/2306.02242 (2023) - [i218]Shuxin Zheng, Jiyan He, Chang Liu, Yu Shi, Ziheng Lu, Weitao Feng, Fusong Ju, Jiaxi Wang, Jianwei Zhu, Yaosen Min, He Zhang, Shidi Tang, Hongxia Hao, Peiran Jin, Chi Chen, Frank Noé, Haiguang Liu, Tie-Yan Liu:
Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning. CoRR abs/2306.05445 (2023) - [i217]Yuchen Fang, Zhenggang Tang, Kan Ren, Weiqing Liu, Li Zhao, Jiang Bian, Dongsheng Li, Weinan Zhang, Yong Yu, Tie-Yan Liu:
Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance. CoRR abs/2307.03119 (2023) - [i216]Qizhi Pei, Kaiyuan Gao, Lijun Wu, Jinhua Zhu, Yingce Xia, Shufang Xie, Tao Qin, Kun He, Tie-Yan Liu, Rui Yan:
FABind: Fast and Accurate Protein-Ligand Binding. CoRR abs/2310.06763 (2023) - 2022
- [j60]Siyuan Liu, Yusong Wang, Yifan Deng, Liang He, Bin Shao, Jian Yin, Nanning Zheng, Tie-Yan Liu, Tong Wang:
Improved drug-target interaction prediction with intermolecular graph transformer. Briefings Bioinform. 23(5) (2022) - [j59]Renqian Luo, Liai Sun, Yingce Xia, Tao Qin, Sheng Zhang, Hoifung Poon, Tie-Yan Liu:
BioGPT: generative pre-trained transformer for biomedical text generation and mining. Briefings Bioinform. 23(6) (2022) - [j58]Lijun Wu, Chengcan Yin, Jinhua Zhu, Zhen Wu, Liang He, Yingce Xia, Shufang Xie, Tao Qin, Tie-Yan Liu:
SPRoBERTa: protein embedding learning with local fragment modeling. Briefings Bioinform. 23(6) (2022) - [j57]Yutai Hou, Yingce Xia, Lijun Wu, Shufang Xie, Yang Fan, Jinhua Zhu, Tao Qin, Tie-Yan Liu:
Discovering drug-target interaction knowledge from biomedical literature. Bioinform. 38(22): 5100-5107 (2022) - [j56]Huishuai Zhang, Da Yu, Mingyang Yi, Wei Chen, Tie-Yan Liu:
Stabilize deep ResNet with a sharp scaling factor τ. Mach. Learn. 111(9): 3359-3392 (2022) - [j55]Xiaobo Liang, Lijun Wu, Juntao Li, Tao Qin, Min Zhang, Tie-Yan Liu:
Multi-Teacher Distillation With Single Model for Neural Machine Translation. IEEE ACM Trans. Audio Speech Lang. Process. 30: 992-1002 (2022) - [j54]Bo Yang, Lijun Wu, Jinhua Zhu, Bo Shao, Xiaola Lin, Tie-Yan Liu:
Multimodal Sentiment Analysis With Two-Phase Multi-Task Learning. IEEE ACM Trans. Audio Speech Lang. Process. 30: 2015-2024 (2022) - [j53]Liang He, Bin Shao, Yanghua Xiao, Yatao Li, Tie-Yan Liu, Enhong Chen, Huanhuan Xia:
Neurally-Guided Semantic Navigation in Knowledge Graph. IEEE Trans. Big Data 8(3): 607-615 (2022) - [j52]Jinhua Zhu, Yingce Xia, Chang Liu, Lijun Wu, Shufang Xie, Yusong Wang, Tong Wang, Tao Qin, Wengang Zhou, Houqiang Li, Haiguang Liu, Tie-Yan Liu:
Direct Molecular Conformation Generation. Trans. Mach. Learn. Res. 2022 (2022) - [c280]Chang Liu, Xu Tan, Chongyang Tao, Zhenxin Fu, Dongyan Zhao, Tie-Yan Liu, Rui Yan:
ProphetChat: Enhancing Dialogue Generation with Simulation of Future Conversation. ACL (1) 2022: 962-973 - [c279]Zhuocheng Gong, Di He, Yelong Shen, Tie-Yan Liu, Weizhu Chen, Dongyan Zhao, Ji-Rong Wen, Rui Yan:
Finding the Dominant Winning Ticket in Pre-Trained Language Models. ACL (Findings) 2022: 1459-1472 - [c278]Yi Ren, Xu Tan, Tao Qin, Zhou Zhao, Tie-Yan Liu:
Revisiting Over-Smoothness in Text to Speech. ACL (1) 2022: 8197-8213 - [c277]Guoqing Liu, Mengzhang Cai, Li Zhao, Tao Qin, Adrian Brown, Jimmy Bischoff, Tie-Yan Liu:
Inspector: Pixel-Based Automated Game Testing via Exploration, Detection, and Investigation. CoG 2022: 237-244 - [c276]Zhiping Luo, Wentao Xu, Weiqing Liu, Jiang Bian, Jian Yin, Tie-Yan Liu:
KGE-CL: Contrastive Learning of Tensor Decomposition Based Knowledge Graph Embeddings. COLING 2022: 2598-2607 - [c275]Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu:
Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart. CVPR 2022: 15202-15212 - [c274]Zeqian Ju, Peiling Lu, Xu Tan, Rui Wang, Chen Zhang, Songruoyao Wu, Kejun Zhang, Xiang-Yang Li, Tao Qin, Tie-Yan Liu:
TeleMelody: Lyric-to-Melody Generation with a Template-Based Two-Stage Method. EMNLP 2022: 5426-5437 - [c273]Shufang Xie, Ang Lv, Yingce Xia, Lijun Wu, Tao Qin, Tie-Yan Liu, Rui Yan:
Target-Side Input Augmentation for Sequence to Sequence Generation. ICLR 2022 - [c272]Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu:
DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting. ICLR 2022 - [c271]Jiawei Huang, Jinglin Chen, Li Zhao, Tao Qin, Nan Jiang, Tie-Yan Liu:
Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality. ICLR 2022 - [c270]Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu:
PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior. ICLR 2022 - [c269]Chongchong Li, Yue Wang, Wei Chen, Yuting Liu, Zhi-Ming Ma, Tie-Yan Liu:
Gradient Information Matters in Policy Optimization by Back-propagating through Model. ICLR 2022 - [c268]Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Nanning Zheng, Bin Shao, Tie-Yan Liu:
SE(3) Equivariant Graph Neural Networks with Complete Local Frames. ICML 2022: 5583-5608 - [c267]Yue Jin, Yue Zhang, Tao Qin, Xudong Zhang, Jian Yuan, Houqiang Li, Tie-Yan Liu:
Supervised Off-Policy Ranking. ICML 2022: 10323-10339 - [c266]Jin Xu, Xu Tan, Kaitao Song, Renqian Luo, Yichong Leng, Tao Qin, Tie-Yan Liu, Jian Li:
Analyzing and Mitigating Interference in Neural Architecture Search. ICML 2022: 24646-24662 - [c265]Yihan Wu, Xu Tan, Bohan Li, Lei He, Sheng Zhao, Ruihua Song, Tao Qin, Tie-Yan Liu:
AdaSpeech 4: Adaptive Text to Speech in Zero-Shot Scenarios. INTERSPEECH 2022: 2568-2572 - [c264]Peiling Lu, Xu Tan, Botao Yu, Tao Qin, Sheng Zhao, Tie-Yan Liu:
MeloForm: Generating Melody with Musical Form based on Expert Systems and Neural Networks. ISMIR 2022: 567-574 - [c263]Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
Availability Attacks Create Shortcuts. KDD 2022: 2367-2376 - [c262]Jinhua Zhu, Yingce Xia, Lijun Wu, Shufang Xie, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu:
Unified 2D and 3D Pre-Training of Molecular Representations. KDD 2022: 2626-2636 - [c261]Chen Zhang, LuChin Chang, Songruoyao Wu, Xu Tan, Tao Qin, Tie-Yan Liu, Kejun Zhang:
ReLyMe: Improving Lyric-to-Melody Generation by Incorporating Lyric-Melody Relationships. ACM Multimedia 2022: 1047-1056 - [c260]Kexun Zhang, Rui Wang, Xu Tan, Junliang Guo, Yi Ren, Tao Qin, Tie-Yan Liu:
A Study of Syntactic Multi-Modality in Non-Autoregressive Machine Translation. NAACL-HLT 2022: 1747-1757 - [c259]Xiaoyu Chen, Xiangming Zhu, Yufeng Zheng, Pushi Zhang, Li Zhao, Wenxue Cheng, Peng Cheng, Yongqiang Xiong, Tao Qin, Jianyu Chen, Tie-Yan Liu:
An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context. NeurIPS 2022 - [c258]Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu:
Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret. NeurIPS 2022 - [c257]Yichong Leng, Zehua Chen, Junliang Guo, Haohe Liu, Jiawei Chen, Xu Tan, Danilo P. Mandic, Lei He, Xiangyang Li, Tao Qin, Sheng Zhao, Tie-Yan Liu:
BinauralGrad: A Two-Stage Conditional Diffusion Probabilistic Model for Binaural Audio Synthesis. NeurIPS 2022 - [c256]Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He:
Your Transformer May Not be as Powerful as You Expect. NeurIPS 2022 - [c255]Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu:
Quantized Training of Gradient Boosting Decision Trees. NeurIPS 2022 - [c254]Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu:
Does Momentum Change the Implicit Regularization on Separable Data? NeurIPS 2022 - [c253]Botao Yu, Peiling Lu, Rui Wang, Wei Hu, Xu Tan, Wei Ye, Shikun Zhang, Tao Qin, Tie-Yan Liu:
Museformer: Transformer with Fine- and Coarse-Grained Attention for Music Generation. NeurIPS 2022 - [i215]Jinhua Zhu, Yingce Xia, Chang Liu, Lijun Wu, Shufang Xie, Tong Wang, Yusong Wang, Wengang Zhou, Tao Qin, Houqiang Li, Tie-Yan Liu:
Direct Molecular Conformation Generation. CoRR abs/2202.01356 (2022) - [i214]Jiawei Huang, Jinglin Chen, Li Zhao, Tao Qin, Nan Jiang, Tie-Yan Liu:
Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality. CoRR abs/2202.06450 (2022) - [i213]Di He, Wenlei Shi, Shanda Li, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu:
Learning Physics-Informed Neural Networks without Stacked Back-propagation. CoRR abs/2202.09340 (2022) - [i212]Lin Huang, Qiyuan Dong, Lijun Wu, Jia Zhang, Jiang Bian, Tie-Yan Liu:
AF2: Adaptive Focus Framework for Aerial Imagery Segmentation. CoRR abs/2202.10322 (2022) - [i211]Lin Huang, Lijun Wu, Jia Zhang, Jiang Bian, Tie-Yan Liu:
Dynamic Relation Discovery and Utilization in Multi-Entity Time Series Forecasting. CoRR abs/2202.10586 (2022) - [i210]Yi Ren, Xu Tan, Tao Qin, Zhou Zhao, Tie-Yan Liu:
Revisiting Over-Smoothness in Text to Speech. CoRR abs/2202.13066 (2022) - [i209]Yu Shi, Shuxin Zheng, Guolin Ke, Yifei Shen, Jiacheng You, Jiyan He, Shengjie Luo, Chang Liu, Di He, Tie-Yan Liu:
Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets. CoRR abs/2203.04810 (2022) - [i208]Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu:
DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting. CoRR abs/2203.07681 (2022) - [i207]Zimeng Li, Shichao Zhu, Bin Shao, Tie-Yan Liu, Xiangxiang Zeng, Tong Wang:
Multi-View Substructure Learning for Drug-Drug Interaction Prediction. CoRR abs/2203.14513 (2022) - [i206]Yihan Wu, Xu Tan, Bohan Li, Lei He, Sheng Zhao, Ruihua Song, Tao Qin, Tie-Yan Liu:
AdaSpeech 4: Adaptive Text to Speech in Zero-Shot Scenarios. CoRR abs/2204.00436 (2022) - [i205]Peiyan Hu, Qi Meng, Bingguang Chen, Shiqi Gong, Yue Wang, Wei Chen, Rongchan Zhu, Zhi-Ming Ma, Tie-Yan Liu:
Neural Operator with Regularity Structure for Modeling Dynamics Driven by SPDEs. CoRR abs/2204.06255 (2022) - [i204]Payal Bajaj, Chenyan Xiong, Guolin Ke, Xiaodong Liu, Di He, Saurabh Tiwary, Tie-Yan Liu, Paul Bennett, Xia Song, Jianfeng Gao:
METRO: Efficient Denoising Pretraining of Large Scale Autoencoding Language Models with Model Generated Signals. CoRR abs/2204.06644 (2022) - [i203]Yisheng Xiao, Lijun Wu, Junliang Guo, Juntao Li, Min Zhang, Tao Qin, Tie-Yan Liu:
A Survey on Non-Autoregressive Generation for Neural Machine Translation and Beyond. CoRR abs/2204.09269 (2022) - [i202]Xu Tan, Jiawei Chen, Haohe Liu, Jian Cong, Chen Zhang, Yanqing Liu, Xi Wang, Yichong Leng, Yuanhao Yi, Lei He, Frank K. Soong, Tao Qin, Sheng Zhao, Tie-Yan Liu:
NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality. CoRR abs/2205.04421 (2022) - [i201]Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu:
Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret. CoRR abs/2205.12418 (2022) - [i200]Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He:
Your Transformer May Not be as Powerful as You Expect. CoRR abs/2205.13401 (2022) - [i199]Yichong Leng, Zehua Chen, Junliang Guo, Haohe Liu, Jiawei Chen, Xu Tan, Danilo P. Mandic, Lei He, Xiang-Yang Li, Tao Qin, Sheng Zhao, Tie-Yan Liu:
BinauralGrad: A Two-Stage Conditional Diffusion Probabilistic Model for Binaural Audio Synthesis. CoRR abs/2205.14807 (2022) - [i198]Da Yu, Gautam Kamath, Janardhan Kulkarni, Tie-Yan Liu, Jian Yin, Huishuai Zhang:
Per-Instance Privacy Accounting for Differentially Private Stochastic Gradient Descent. CoRR abs/2206.02617 (2022) - [i197]Wenlei Shi, Xinquan Huang, Xiaotian Gao, Xinran Wei, Jia Zhang, Jiang Bian, Mao Yang, Tie-Yan Liu:
LordNet: Learning to Solve Parametric Partial Differential Equations without Simulated Data. CoRR abs/2206.09418 (2022) - [i196]Rui Zhang, Peiyan Hu, Qi Meng, Yue Wang, Rongchan Zhu, Bingguang Chen, Zhi-Ming Ma, Tie-Yan Liu:
Deep Random Vortex Method for Simulation and Inference of Navier-Stokes Equations. CoRR abs/2206.09571 (2022) - [i195]Qizhi Pei, Lijun Wu, Jinhua Zhu, Yingce Xia, Shufang Xie, Tao Qin, Haiguang Liu, Tie-Yan Liu:
SMT-DTA: Improving Drug-Target Affinity Prediction with Semi-supervised Multi-task Training. CoRR abs/2206.09818 (2022) - [i194]Xiaodong Yang, Huishuai Zhang, Wei Chen, Tie-Yan Liu:
Normalized/Clipped SGD with Perturbation for Differentially Private Non-Convex Optimization. CoRR abs/2206.13033 (2022) - [i193]Kexun Zhang, Rui Wang, Xu Tan, Junliang Guo, Yi Ren, Tao Qin, Tie-Yan Liu:
A Study of Syntactic Multi-Modality in Non-Autoregressive Machine Translation. CoRR abs/2207.04206 (2022) - [i192]Chen Zhang, LuChin Chang, Songruoyao Wu, Xu Tan, Tao Qin, Tie-Yan Liu, Kejun Zhang:
ReLyMe: Improving Lyric-to-Melody Generation by Incorporating Lyric-Melody Relationships. CoRR abs/2207.05688 (2022) - [i191]Guoqing Liu, Mengzhang Cai, Li Zhao, Tao Qin, Adrian Brown, Jimmy Bischoff, Tie-Yan Liu:
Inspector: Pixel-Based Automated Game Testing via Exploration, Detection, and Investigation. CoRR abs/2207.08379 (2022) - [i190]Jinhua Zhu, Yingce Xia, Lijun Wu, Shufang Xie, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu:
Unified 2D and 3D Pre-Training of Molecular Representations. CoRR abs/2207.08806 (2022) - [i189]Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu:
Quantized Training of Gradient Boosting Decision Trees. CoRR abs/2207.09682 (2022) - [i188]Ang Lv, Xu Tan, Tao Qin, Tie-Yan Liu, Rui Yan:
Re-creation of Creations: A New Paradigm for Lyric-to-Melody Generation. CoRR abs/2208.05697 (2022) - [i187]Bohan Wang, Yushun Zhang, Huishuai Zhang, Qi Meng, Zhi-Ming Ma, Tie-Yan Liu, Wei Chen:
Provable Adaptivity in Adam. CoRR abs/2208.09900 (2022) - [i186]Peiling Lu, Xu Tan, Botao Yu, Tao Qin, Sheng Zhao, Tie-Yan Liu:
MeloForm: Generating Melody with Musical Form based on Expert Systems and Neural Networks. CoRR abs/2208.14345 (2022) - [i185]Kehan Wu, Yingce Xia, Yang Fan, Pan Deng, Haiguang Liu, Lijun Wu, Shufang Xie, Tong Wang, Tao Qin, Tie-Yan Liu:
Tailoring Molecules for Protein Pockets: a Transformer-based Generative Solution for Structured-based Drug Design. CoRR abs/2209.06158 (2022) - [i184]Shengjie Luo, Tianlang Chen, Yixian Xu, Shuxin Zheng, Tie-Yan Liu, Di He, Liwei Wang:
One Transformer Can Understand Both 2D & 3D Molecular Data. CoRR abs/2210.01765 (2022) - [i183]Mingqing Xiao, Shuxin Zheng, Chang Liu, Zhouchen Lin, Tie-Yan Liu:
Invertible Rescaling Network and Its Extensions. CoRR abs/2210.04188 (2022) - [i182]Renqian Luo, Liai Sun, Yingce Xia, Tao Qin, Sheng Zhang, Hoifung Poon, Tie-Yan Liu:
BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining. CoRR abs/2210.10341 (2022) - [i181]Botao Yu, Peiling Lu, Rui Wang, Wei Hu, Xu Tan, Wei Ye, Shikun Zhang, Tao Qin, Tie-Yan Liu:
Museformer: Transformer with Fine- and Coarse-Grained Attention for Music Generation. CoRR abs/2210.10349 (2022) - [i180]Kaiyuan Gao, Lijun Wu, Jinhua Zhu, Tianbo Peng, Yingce Xia, Liang He, Shufang Xie, Tao Qin, Haiguang Liu, Kun He, Tie-Yan Liu:
Incorporating Pre-training Paradigm for Antibody Sequence-Structure Co-design. CoRR abs/2211.08406 (2022) - [i179]Yusong Wang, Shaoning Li, Tong Wang, Zun Wang, Xinheng He, Bin Shao, Tie-Yan Liu:
An ensemble of VisNet, Transformer-M, and pretraining models for molecular property prediction in OGB Large-Scale Challenge @ NeurIPS 2022. CoRR abs/2211.12791 (2022) - [i178]Yichong Leng, Xu Tan, Wenjie Liu, Kaitao Song, Rui Wang, Xiang-Yang Li, Tao Qin, Edward Lin, Tie-Yan Liu:
SoftCorrect: Error Correction with Soft Detection for Automatic Speech Recognition. CoRR abs/2212.01039 (2022) - [i177]Xiaoyu Chen, Xiangming Zhu, Yufeng Zheng, Pushi Zhang, Li Zhao, Wenxue Cheng, Peng Cheng, Yongqiang Xiong, Tao Qin, Jianyu Chen, Tie-Yan Liu:
An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context. CoRR abs/2212.12735 (2022) - 2021
- [j51]Wenze Ding, Qijiang Xu, Siyuan Liu, Tong Wang, Bin Shao, Haipeng Gong, Tie-Yan Liu:
SAMF: a self-adaptive protein modeling framework. Bioinform. 37(22): 4075-4082 (2021) - [j50]Siyuan Liu, Tong Wang, Qijiang Xu, Bin Shao, Jian Yin, Tie-Yan Liu:
Complementing sequence-derived features with structural information extracted from fragment libraries for protein structure prediction. BMC Bioinform. 22(1): 351 (2021) - [j49]Zhumin Chen, Xueqi Cheng, Shoubin Dong, Zhicheng Dou, Jiafeng Guo, Xuanjing Huang, Yanyan Lan, Chenliang Li, Ru Li, Tie-Yan Liu, Yiqun Liu, Jun Ma, Bing Qin, Mingwen Wang, Ji-Rong Wen, Jun Xu, Min Zhang, Peng Zhang, Qi Zhang:
Information retrieval: a view from the Chinese IR community. Frontiers Comput. Sci. 15(1): 151601 (2021) - [j48]Guoqing Liu, Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu:
Demonstration actor critic. Neurocomputing 434: 194-202 (2021) - [j47]Zhibing Zhao, Yingce Xia, Tao Qin, Lirong Xia, Tie-Yan Liu:
Dual Learning: Theoretical Study and an Algorithmic Extension. SN Comput. Sci. 2(5): 413 (2021) - [c252]Yuchen Fang, Kan Ren, Weiqing Liu, Dong Zhou, Weinan Zhang, Jiang Bian, Yong Yu, Tie-Yan Liu:
Universal Trading for Order Execution with Oracle Policy Distillation. AAAI 2021: 107-115 - [c251]Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
How Does Data Augmentation Affect Privacy in Machine Learning? AAAI 2021: 10746-10753 - [c250]Chen Zhang, Xu Tan, Yi Ren, Tao Qin, Kejun Zhang, Tie-Yan Liu:
UWSpeech: Speech to Speech Translation for Unwritten Languages. AAAI 2021: 14319-14327 - [c249]Lanqing Xue, Kaitao Song, Duocai Wu, Xu Tan, Nevin L. Zhang, Tao Qin, Wei-Qiang Zhang, Tie-Yan Liu:
DeepRapper: Neural Rap Generation with Rhyme and Rhythm Modeling. ACL/IJCNLP (1) 2021: 69-81 - [c248]Mingliang Zeng, Xu Tan, Rui Wang, Zeqian Ju, Tao Qin, Tie-Yan Liu:
MusicBERT: Symbolic Music Understanding with Large-Scale Pre-Training. ACL/IJCNLP (Findings) 2021: 791-800 - [c247]Wenlei Shi, Xinran Wei, Jia Zhang, Xiaoyuan Ni, Arthur Jiang, Jiang Bian, Tie-Yan Liu:
Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations. AAMAS 2021: 1191-1199 - [c246]Min Hou, Chang Xu, Yang Liu, Weiqing Liu, Jiang Bian, Le Wu, Zhi Li, Enhong Chen, Tie-Yan Liu:
Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion. CIKM 2021: 700-709 - [c245]Shun Zheng, Zhifeng Gao, Wei Cao, Jiang Bian, Tie-Yan Liu:
HierST: A Unified Hierarchical Spatial-temporal Framework for COVID-19 Trend Forecasting. CIKM 2021: 4383-4392 - [c244]Shuqi Lu, Di He, Chenyan Xiong, Guolin Ke, Waleed Malik, Zhicheng Dou, Paul Bennett, Tie-Yan Liu, Arnold Overwijk:
Less is More: Pretrain a Strong Siamese Encoder for Dense Text Retrieval Using a Weak Decoder. EMNLP (1) 2021: 2780-2791 - [c243]Yichong Leng, Xu Tan, Rui Wang, Linchen Zhu, Jin Xu, Wenjie Liu, Linquan Liu, Xiang-Yang Li, Tao Qin, Edward Lin, Tie-Yan Liu:
FastCorrect 2: Fast Error Correction on Multiple Candidates for Automatic Speech Recognition. EMNLP (Findings) 2021: 4328-4337 - [c242]Renqian Luo, Xu Tan, Rui Wang, Tao Qin, Jinzhu Li, Sheng Zhao, Enhong Chen, Tie-Yan Liu:
Lightspeech: Lightweight and Fast Text to Speech with Neural Architecture Search. ICASSP 2021: 5699-5703 - [c241]Yuzi Yan, Xu Tan, Bohan Li, Tao Qin, Sheng Zhao, Yuan Shen, Tie-Yan Liu:
Adaspeech 2: Adaptive Text to Speech with Untranscribed Data. ICASSP 2021: 6613-6617 - [c240]Chen Zhang, Yi Ren, Xu Tan, Jinglin Liu, Kejun Zhang, Tao Qin, Sheng Zhao, Tie-Yan Liu:
Denoispeech: Denoising Text to Speech with Frame-Level Noise Modeling. ICASSP 2021: 7063-7067 - [c239]Qiyu Wu, Chen Xing, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu:
Taking Notes on the Fly Helps Language Pre-Training. ICLR 2021 - [c238]Yi Ren, Chenxu Hu, Xu Tan, Tao Qin, Sheng Zhao, Zhou Zhao, Tie-Yan Liu:
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech. ICLR 2021 - [c237]Mingjian Chen, Xu Tan, Bohan Li, Yanqing Liu, Tao Qin, Sheng Zhao, Tie-Yan Liu:
AdaSpeech: Adaptive Text to Speech for Custom Voice. ICLR 2021 - [c236]Guolin Ke, Di He, Tie-Yan Liu:
Rethinking Positional Encoding in Language Pre-training. ICLR 2021 - [c235]Guoqing Liu, Chuheng Zhang, Li Zhao, Tao Qin, Jinhua Zhu, Jian Li, Nenghai Yu, Tie-Yan Liu:
Return-Based Contrastive Representation Learning for Reinforcement Learning. ICLR 2021 - [c234]Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu:
Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning. ICLR 2021 - [c233]Jinhua Zhu, Lijun Wu, Yingce Xia, Shufang Xie, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu:
IOT: Instance-wise Layer Reordering for Transformer Structures. ICLR 2021 - [c232]Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang:
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training. ICML 2021: 1204-1215 - [c231]Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu:
How could Neural Networks understand Programs? ICML 2021: 8476-8486 - [c230]Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu:
The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks. ICML 2021: 10849-10858 - [c229]Xueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu, Shufang Xie, Tao Qin, Tie-Yan Liu:
Temporally Correlated Task Scheduling for Sequence Learning. ICML 2021: 11274-11284 - [c228]Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
Large Scale Private Learning via Low-rank Reparametrization. ICML 2021: 12208-12218 - [c227]Tianhao Zhang, Qiwei Ye, Jiang Bian, Guangming Xie, Tie-Yan Liu:
MFVFD: A Multi-Agent Q-Learning Approach to Cooperative and Non-Cooperative Tasks. IJCAI 2021: 500-506 - [c226]Pushi Zhang, Li Zhao, Guoqing Liu, Jiang Bian, Minlie Huang, Tao Qin, Tie-Yan Liu:
Independence-aware Advantage Estimation. IJCAI 2021: 3349-3355 - [c225]Rui Wang, Xu Tan, Renqian Luo, Tao Qin, Tie-Yan Liu:
A Survey on Low-Resource Neural Machine Translation. IJCAI 2021: 4636-4643 - [c224]Yuzi Yan, Xu Tan, Bohan Li, Guangyan Zhang, Tao Qin, Sheng Zhao, Yuan Shen, Wei-Qiang Zhang, Tie-Yan Liu:
Adaptive Text to Speech for Spontaneous Style. Interspeech 2021: 4668-4672 - [c223]Jin Xu, Xu Tan, Renqian Luo, Kaitao Song, Jian Li, Tao Qin, Tie-Yan Liu:
NAS-BERT: Task-Agnostic and Adaptive-Size BERT Compression with Neural Architecture Search. KDD 2021: 1933-1943 - [c222]Zhen Wu, Lijun Wu, Qi Meng, Yingce Xia, Shufang Xie, Tao Qin, Xinyu Dai, Tie-Yan Liu:
UniDrop: A Simple yet Effective Technique to Improve Transformer without Extra Cost. NAACL-HLT 2021: 3865-3878 - [c221]Abhishek Das, Muhammed Shuaibi, Aini Palizhati, Siddharth Goyal, Aditya Grover, Adeesh Kolluru, Janice Lan, Ammar Rizvi, Anuroop Sriram, Brandon M. Wood, Devi Parikh, Zachary W. Ulissi, C. Lawrence Zitnick, Guolin Ke, Shuxin Zheng, Yu Shi, Di He, Tie-Yan Liu, Chengxuan Ying, Jiacheng You, Yihan He, Rostislav Grigoriev, Ruslan Lukin, Adel Yarullin, Max Faleev:
The Open Catalyst Challenge 2021: Competition Report. NeurIPS (Competition and Demos) 2021: 29-40 - [c220]Pushi Zhang, Xiaoyu Chen, Li Zhao, Wei Xiong, Tao Qin, Tie-Yan Liu:
Distributional Reinforcement Learning for Multi-Dimensional Reward Functions. NeurIPS 2021: 1519-1529 - [c219]Jongjin Park, Younggyo Seo, Chang Liu, Li Zhao, Tao Qin, Jinwoo Shin, Tie-Yan Liu:
Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning. NeurIPS 2021: 3029-3042 - [c218]Chang Liu, Xinwei Sun, Jindong Wang, Haoyue Tang, Tao Li, Tao Qin, Wei Chen, Tie-Yan Liu:
Learning Causal Semantic Representation for Out-of-Distribution Prediction. NeurIPS 2021: 6155-6170 - [c217]Minghuan Liu, Hanye Zhao, Zhengyu Yang, Jian Shen, Weinan Zhang, Li Zhao, Tie-Yan Liu:
Curriculum Offline Imitating Learning. NeurIPS 2021: 6266-6277 - [c216]Jiawei Chen, Xu Tan, Yichong Leng, Jin Xu, Guihua Wen, Tao Qin, Tie-Yan Liu:
Speech-T: Transducer for Text to Speech and Beyond. NeurIPS 2021: 6621-6633 - [c215]Xiaobo Liang, Lijun Wu, Juntao Li, Yue Wang, Qi Meng, Tao Qin, Wei Chen, Min Zhang, Tie-Yan Liu:
R-Drop: Regularized Dropout for Neural Networks. NeurIPS 2021: 10890-10905 - [c214]He Zhang, Fusong Ju, Jianwei Zhu, Liang He, Bin Shao, Nanning Zheng, Tie-Yan Liu:
Co-evolution Transformer for Protein Contact Prediction. NeurIPS 2021: 14252-14263 - [c213]Xinwei Sun, Botong Wu, Xiangyu Zheng, Chang Liu, Wei Chen, Tao Qin, Tie-Yan Liu:
Recovering Latent Causal Factor for Generalization to Distributional Shifts. NeurIPS 2021: 16846-16859 - [c212]Yichong Leng, Xu Tan, Linchen Zhu, Jin Xu, Renqian Luo, Linquan Liu, Tao Qin, Xiangyang Li, Edward Lin, Tie-Yan Liu:
FastCorrect: Fast Error Correction with Edit Alignment for Automatic Speech Recognition. NeurIPS 2021: 21708-21719 - [c211]Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu:
Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding. NeurIPS 2021: 22795-22807 - [c210]Bohan Wang, Huishuai Zhang, Jieyu Zhang, Qi Meng, Wei Chen, Tie-Yan Liu:
Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD. NeurIPS 2021: 26080-26090 - [c209]Jinpeng Li, Yingce Xia, Rui Yan, Hongda Sun, Dongyan Zhao, Tie-Yan Liu:
Stylized Dialogue Generation with Multi-Pass Dual Learning. NeurIPS 2021: 28470-28481 - [c208]Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu:
Do Transformers Really Perform Badly for Graph Representation? NeurIPS 2021: 28877-28888 - [c207]Chang Liu, Haoyue Tang, Tao Qin, Jintao Wang, Tie-Yan Liu:
On the Generative Utility of Cyclic Conditionals. NeurIPS 2021: 30242-30256 - [c206]Xufang Luo, Qi Meng, Wei Chen, Yunhong Wang, Tie-Yan Liu:
Path-BN: Towards effective batch normalization in the Path Space for ReLU networks. UAI 2021: 834-843 - [c205]Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu:
REST: Relational Event-driven Stock Trend Forecasting. WWW 2021: 1-10 - [i176]Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu:
BN-invariant sharpness regularizes the training model to better generalization. CoRR abs/2101.02944 (2021) - [i175]Renqian Luo, Xu Tan, Rui Wang, Tao Qin, Jinzhu Li, Sheng Zhao, Enhong Chen, Tie-Yan Liu:
LightSpeech: Lightweight and Fast Text to Speech with Neural Architecture Search. CoRR abs/2102.04040 (2021) - [i174]Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu:
REST: Relational Event-driven Stock Trend Forecasting. CoRR abs/2102.07372 (2021) - [i173]Shengjie Luo, Kaiyuan Gao, Shuxin Zheng, Guolin Ke, Di He, Liwei Wang, Tie-Yan Liu:
Revisiting Language Encoding in Learning Multilingual Representations. CoRR abs/2102.08357 (2021) - [i172]Shuqi Lu, Chenyan Xiong, Di He, Guolin Ke, Waleed Malik, Zhicheng Dou, Paul Bennett, Tie-Yan Liu, Arnold Overwijk:
Less is More: Pre-training a Strong Siamese Encoder Using a Weak Decoder. CoRR abs/2102.09206 (2021) - [i171]Guoqing Liu, Chuheng Zhang, Li Zhao, Tao Qin, Jinhua Zhu, Jian Li, Nenghai Yu, Tie-Yan Liu:
Return-Based Contrastive Representation Learning for Reinforcement Learning. CoRR abs/2102.10960 (2021) - [i170]Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu:
Do Not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning. CoRR abs/2102.12677 (2021) - [i169]Chengxuan Ying, Guolin Ke, Di He, Tie-Yan Liu:
LazyFormer: Self Attention with Lazy Update. CoRR abs/2102.12702 (2021) - [i168]Mingjian Chen, Xu Tan, Bohan Li, Yanqing Liu, Tao Qin, Sheng Zhao, Tie-Yan Liu:
AdaSpeech: Adaptive Text to Speech for Custom Voice. CoRR abs/2103.00993 (2021) - [i167]Jinhua Zhu, Lijun Wu, Yingce Xia, Shufang Xie, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu:
IOT: Instance-wise Layer Reordering for Transformer Structures. CoRR abs/2103.03457 (2021) - [i166]Jindong Wang, Wenjie Feng, Chang Liu, Chaohui Yu, Mingxuan Du, Renjun Xu, Tao Qin, Tie-Yan Liu:
Learning Invariant Representations across Domains and Tasks. CoRR abs/2103.05114 (2021) - [i165]Yuchen Fang, Kan Ren, Weiqing Liu, Dong Zhou, Weinan Zhang, Jiang Bian, Yong Yu, Tie-Yan Liu:
Universal Trading for Order Execution with Oracle Policy Distillation. CoRR abs/2103.10860 (2021) - [i164]Zhen Wu, Lijun Wu, Qi Meng, Yingce Xia, Shufang Xie, Tao Qin, Xinyu Dai, Tie-Yan Liu:
UniDrop: A Simple yet Effective Technique to Improve Transformer without Extra Cost. CoRR abs/2104.04946 (2021) - [i163]Yuzi Yan, Xu Tan, Bohan Li, Tao Qin, Sheng Zhao, Yuan Shen, Tie-Yan Liu:
AdaSpeech 2: Adaptive Text to Speech with Untranscribed Data. CoRR abs/2104.09715 (2021) - [i162]Yichong Leng, Xu Tan, Linchen Zhu, Jin Xu, Renqian Luo, Linquan Liu, Tao Qin, Xiang-Yang Li, Edward Lin, Tie-Yan Liu:
FastCorrect: Fast Error Correction with Edit Alignment for Automatic Speech Recognition. CoRR abs/2105.03842 (2021) - [i161]Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu:
How could Neural Networks understand Programs? CoRR abs/2105.04297 (2021) - [i160]Jinhui Yuan, Fei Pan, Chunting Zhou, Tao Qin, Tie-Yan Liu:
Learning Structures for Deep Neural Networks. CoRR abs/2105.13905 (2021) - [i159]Jin Xu, Xu Tan, Renqian Luo, Kaitao Song, Jian Li, Tao Qin, Tie-Yan Liu:
NAS-BERT: Task-Agnostic and Adaptive-Size BERT Compression with Neural Architecture Search. CoRR abs/2105.14444 (2021) - [i158]Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu:
Adversarial Training with Rectified Rejection. CoRR abs/2105.14785 (2021) - [i157]Ziming Liu, Bohan Wang, Qi Meng, Wei Chen, Max Tegmark, Tie-Yan Liu:
Machine-Learning Non-Conservative Dynamics for New-Physics Detection. CoRR abs/2106.00026 (2021) - [i156]Shiqi Gong, Qi Meng, Yue Wang, Lijun Wu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu:
Incorporating NODE with Pre-trained Neural Differential Operator for Learning Dynamics. CoRR abs/2106.04166 (2021) - [i155]Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu:
Do Transformers Really Perform Bad for Graph Representation? CoRR abs/2106.05234 (2021) - [i154]Mingliang Zeng, Xu Tan, Rui Wang, Zeqian Ju, Tao Qin, Tie-Yan Liu:
MusicBERT: Symbolic Music Understanding with Large-Scale Pre-Training. CoRR abs/2106.05630 (2021) - [i153]Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu:
PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Driven Adaptive Prior. CoRR abs/2106.06406 (2021) - [i152]Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
Large Scale Private Learning via Low-rank Reparametrization. CoRR abs/2106.09352 (2021) - [i151]Jinhua Zhu, Yingce Xia, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu:
Dual-view Molecule Pre-training. CoRR abs/2106.10234 (2021) - [i150]Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu:
Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding. CoRR abs/2106.12566 (2021) - [i149]Xiaobo Liang, Lijun Wu, Juntao Li, Yue Wang, Qi Meng, Tao Qin, Wei Chen, Min Zhang, Tie-Yan Liu:
R-Drop: Regularized Dropout for Neural Networks. CoRR abs/2106.14448 (2021) - [i148]Yichi Zhou, Shihong Song, Huishuai Zhang, Jun Zhu, Wei Chen, Tie-Yan Liu:
Regularized OFU: an Efficient UCB Estimator forNon-linear Contextual Bandit. CoRR abs/2106.15128 (2021) - [i147]Xu Tan, Tao Qin, Frank K. Soong, Tie-Yan Liu:
A Survey on Neural Speech Synthesis. CoRR abs/2106.15561 (2021) - [i146]Chang Liu, Haoyue Tang, Tao Qin, Jintao Wang, Tie-Yan Liu:
On the Generative Utility of Cyclic Conditionals. CoRR abs/2106.15962 (2021) - [i145]Yue Jin, Yue Zhang, Tao Qin, Xudong Zhang, Jian Yuan, Houqiang Li, Tie-Yan Liu:
Supervised Off-Policy Ranking. CoRR abs/2107.01360 (2021) - [i144]Lanqing Xue, Kaitao Song, Duocai Wu, Xu Tan, Nevin L. Zhang, Tao Qin, Wei-Qiang Zhang, Tie-Yan Liu:
DeepRapper: Neural Rap Generation with Rhyme and Rhythm Modeling. CoRR abs/2107.01875 (2021) - [i143]Xiangyu Zheng, Xinwei Sun, Wei Chen, Tie-Yan Liu:
Causally Invariant Predictor with Shift-Robustness. CoRR abs/2107.01876 (2021) - [i142]Yuzi Yan, Xu Tan, Bohan Li, Guangyan Zhang, Tao Qin, Sheng Zhao, Yuan Shen, Wei-Qiang Zhang, Tie-Yan Liu:
AdaSpeech 3: Adaptive Text to Speech for Spontaneous Style. CoRR abs/2107.02530 (2021) - [i141]Rui Wang, Xu Tan, Renqian Luo, Tao Qin, Tie-Yan Liu:
A Survey on Low-Resource Neural Machine Translation. CoRR abs/2107.04239 (2021) - [i140]Jin Xu, Xu Tan, Kaitao Song, Renqian Luo, Yichong Leng, Tao Qin, Tie-Yan Liu, Jian Li:
Analyzing and Mitigating Interference in Neural Architecture Search. CoRR abs/2108.12821 (2021) - [i139]Wentao Xu, Weiqing Liu, Jiang Bian, Jian Yin, Tie-Yan Liu:
Instance-wise Graph-based Framework for Multivariate Time Series Forecasting. CoRR abs/2109.06489 (2021) - [i138]Zeqian Ju, Peiling Lu, Xu Tan, Rui Wang, Chen Zhang, Songruoyao Wu, Kejun Zhang, Xiangyang Li, Tao Qin, Tie-Yan Liu:
TeleMelody: Lyric-to-Melody Generation with a Template-Based Two-Stage Method. CoRR abs/2109.09617 (2021) - [i137]Yutai Hou, Yingce Xia, Lijun Wu, Shufang Xie, Yang Fan, Jinhua Zhu, Wanxiang Che, Tao Qin, Tie-Yan Liu:
Discovering Drug-Target Interaction Knowledge from Biomedical Literature. CoRR abs/2109.13187 (2021) - [i136]Yichong Leng, Xu Tan, Rui Wang, Linchen Zhu, Jin Xu, Linquan Liu, Tao Qin, Xiang-Yang Li, Edward Lin, Tie-Yan Liu:
FastCorrect 2: Fast Error Correction on Multiple Candidates for Automatic Speech Recognition. CoRR abs/2109.14420 (2021) - [i135]Siyuan Liu, Yusong Wang, Tong Wang, Yifan Deng, Liang He, Bin Shao, Jian Yin, Nanning Zheng, Tie-Yan Liu:
Improved Drug-target Interaction Prediction with Intermolecular Graph Transformer. CoRR abs/2110.07347 (2021) - [i134]Pushi Zhang, Xiaoyu Chen, Li Zhao, Wei Xiong, Tao Qin, Tie-Yan Liu:
Distributional Reinforcement Learning for Multi-Dimensional Reward Functions. CoRR abs/2110.13578 (2021) - [i133]Wentao Xu, Weiqing Liu, Lewen Wang, Yingce Xia, Jiang Bian, Jian Yin, Tie-Yan Liu:
HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information. CoRR abs/2110.13716 (2021) - [i132]Bohan Wang, Huishuai Zhang, Jieyu Zhang, Qi Meng, Wei Chen, Tie-Yan Liu:
Optimizing Information-theoretical Generalization Bounds via Anisotropic Noise in SGLD. CoRR abs/2110.13750 (2021) - [i131]Jongjin Park, Younggyo Seo, Chang Liu, Li Zhao, Tao Qin, Jinwoo Shin, Tie-Yan Liu:
Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning. CoRR abs/2110.14118 (2021) - [i130]Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Bin Shao, Tie-Yan Liu:
Equivariant vector field network for many-body system modeling. CoRR abs/2110.14811 (2021) - [i129]Liang He, Shizhuo Zhang, Lijun Wu, Huanhuan Xia, Fusong Ju, He Zhang, Siyuan Liu, Yingce Xia, Jianwei Zhu, Pan Deng, Bin Shao, Tao Qin, Tie-Yan Liu:
Pre-training Co-evolutionary Protein Representation via A Pairwise Masked Language Model. CoRR abs/2110.15527 (2021) - [i128]Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
Indiscriminate Poisoning Attacks Are Shortcuts. CoRR abs/2111.00898 (2021) - [i127]Minghuan Liu, Hanye Zhao, Zhengyu Yang, Jian Shen, Weinan Zhang, Li Zhao, Tie-Yan Liu:
Curriculum Offline Imitation Learning. CoRR abs/2111.02056 (2021) - [i126]Wentao Xu, Zhiping Luo, Weiqing Liu, Jiang Bian, Jian Yin, Tie-Yan Liu:
KGE-CL: Contrastive Learning of Knowledge Graph Embeddings. CoRR abs/2112.04871 (2021) - [i125]Wentao Xu, Yingce Xia, Weiqing Liu, Jiang Bian, Jian Yin, Tie-Yan Liu:
SHGNN: Structure-Aware Heterogeneous Graph Neural Network. CoRR abs/2112.06244 (2021) - 2020
- [j46]Yue Wang, Yuting Liu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu:
Target transfer Q-learning and its convergence analysis. Neurocomputing 392: 11-22 (2020) - [j45]Yang Fan, Fei Tian, Yingce Xia, Tao Qin, Xiang-Yang Li, Tie-Yan Liu:
Searching Better Architectures for Neural Machine Translation. IEEE ACM Trans. Audio Speech Lang. Process. 28: 1574-1585 (2020) - [j44]Wenzheng Hu, Junqi Jin, Tie-Yan Liu, Changshui Zhang:
Automatically Design Convolutional Neural Networks by Optimization With Submodularity and Supermodularity. IEEE Trans. Neural Networks Learn. Syst. 31(9): 3215-3229 (2020) - [j43]Shicong Cen, Huishuai Zhang, Yuejie Chi, Wei Chen, Tie-Yan Liu:
Convergence of Distributed Stochastic Variance Reduced Methods Without Sampling Extra Data. IEEE Trans. Signal Process. 68: 3976-3989 (2020) - [c204]Yiren Wang, Lijun Wu, Yingce Xia, Tao Qin, ChengXiang Zhai, Tie-Yan Liu:
Transductive Ensemble Learning for Neural Machine Translation. AAAI 2020: 6291-6298 - [c203]Zhenhui Xu, Guolin Ke, Jia Zhang, Jiang Bian, Tie-Yan Liu:
Light Multi-Segment Activation for Model Compression. AAAI 2020: 6542-6549 - [c202]Junliang Guo, Xu Tan, Linli Xu, Tao Qin, Enhong Chen, Tie-Yan Liu:
Fine-Tuning by Curriculum Learning for Non-Autoregressive Neural Machine Translation. AAAI 2020: 7839-7846 - [c201]Yi Ren, Jinglin Liu, Xu Tan, Zhou Zhao, Sheng Zhao, Tie-Yan Liu:
A Study of Non-autoregressive Model for Sequence Generation. ACL 2020: 149-159 - [c200]Yi Ren, Jinglin Liu, Xu Tan, Chen Zhang, Tao Qin, Zhou Zhao, Tie-Yan Liu:
SimulSpeech: End-to-End Simultaneous Speech to Text Translation. ACL 2020: 3787-3796 - [c199]Wentao Xu, Shun Zheng, Liang He, Bin Shao, Jian Yin, Tie-Yan Liu:
SEEK: Segmented Embedding of Knowledge Graphs. ACL 2020: 3888-3897 - [c198]Zhibing Zhao, Yingce Xia, Tao Qin, Lirong Xia, Tie-Yan Liu:
Dual Learning: Theoretical Study and an Algorithmic Extension. ACML 2020: 321-336 - [c197]Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu:
Invertible Image Rescaling. ECCV (1) 2020: 126-144 - [c196]Zhining Liu, Wei Cao, Zhifeng Gao, Jiang Bian, Hechang Chen, Yi Chang, Tie-Yan Liu:
Self-paced Ensemble for Highly Imbalanced Massive Data Classification. ICDE 2020: 841-852 - [c195]Jinhua Zhu, Yingce Xia, Lijun Wu, Di He, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu:
Incorporating BERT into Neural Machine Translation. ICLR 2020 - [c194]Lijun Wu, Shufang Xie, Yingce Xia, Yang Fan, Jian-Huang Lai, Tao Qin, Tie-Yan Liu:
Sequence Generation with Mixed Representations. ICML 2020: 10388-10398 - [c193]Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tie-Yan Liu:
On Layer Normalization in the Transformer Architecture. ICML 2020: 10524-10533 - [c192]Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
Gradient Perturbation is Underrated for Differentially Private Convex Optimization. IJCAI 2020: 3117-3123 - [c191]Jinglin Liu, Yi Ren, Xu Tan, Chen Zhang, Tao Qin, Zhou Zhao, Tie-Yan Liu:
Task-Level Curriculum Learning for Non-Autoregressive Neural Machine Translation. IJCAI 2020: 3861-3867 - [c190]Yi Ren, Xu Tan, Tao Qin, Jian Luan, Zhou Zhao, Tie-Yan Liu:
DeepSinger: Singing Voice Synthesis with Data Mined From the Web. KDD 2020: 1979-1989 - [c189]Jin Xu, Xu Tan, Yi Ren, Tao Qin, Jian Li, Sheng Zhao, Tie-Yan Liu:
LRSpeech: Extremely Low-Resource Speech Synthesis and Recognition. KDD 2020: 2802-2812 - [c188]Yi Ren, Jinzheng He, Xu Tan, Tao Qin, Zhou Zhao, Tie-Yan Liu:
PopMAG: Pop Music Accompaniment Generation. ACM Multimedia 2020: 1198-1206 - [c187]Weicong Chen, Xu Tan, Yingce Xia, Tao Qin, Yu Wang, Tie-Yan Liu:
DualLip: A System for Joint Lip Reading and Generation. ACM Multimedia 2020: 1985-1993 - [c186]Zichuan Lin, Derek Yang, Li Zhao, Tao Qin, Guangwen Yang, Tie-Yan Liu:
RD$^2$: Reward Decomposition with Representation Decomposition. NeurIPS 2020 - [c185]Renqian Luo, Xu Tan, Rui Wang, Tao Qin, Enhong Chen, Tie-Yan Liu:
Semi-Supervised Neural Architecture Search. NeurIPS 2020 - [c184]Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, Tie-Yan Liu:
MPNet: Masked and Permuted Pre-training for Language Understanding. NeurIPS 2020 - [e8]Yennun Huang, Irwin King, Tie-Yan Liu, Maarten van Steen:
WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020. ACM / IW3C2 2020, ISBN 978-1-4503-7023-3 [contents] - [e7]Amal El Fallah Seghrouchni, Gita Sukthankar, Tie-Yan Liu, Maarten van Steen:
Companion of The 2020 Web Conference 2020, Taipei, Taiwan, April 20-24, 2020. ACM / IW3C2 2020, ISBN 978-1-4503-7024-0 [contents] - [i124]Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tie-Yan Liu:
On Layer Normalization in the Transformer Architecture. CoRR abs/2002.04745 (2020) - [i123]Jinhua Zhu, Yingce Xia, Lijun Wu, Di He, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu:
Incorporating BERT into Neural Machine Translation. CoRR abs/2002.06823 (2020) - [i122]Renqian Luo, Xu Tan, Rui Wang, Tao Qin, Enhong Chen, Tie-Yan Liu:
Semi-Supervised Neural Architecture Search. CoRR abs/2002.10389 (2020) - [i121]Junjie Li, Sotetsu Koyamada, Qiwei Ye, Guoqing Liu, Chao Wang, Ruihan Yang, Li Zhao, Tao Qin, Tie-Yan Liu, Hsiao-Wuen Hon:
Suphx: Mastering Mahjong with Deep Reinforcement Learning. CoRR abs/2003.13590 (2020) - [i120]Yuxuan Song, Qiwei Ye, Minkai Xu, Tie-Yan Liu:
Discriminator Contrastive Divergence: Semi-Amortized Generative Modeling by Exploring Energy of the Discriminator. CoRR abs/2004.01704 (2020) - [i119]Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, Tie-Yan Liu:
MPNet: Masked and Permuted Pre-training for Language Understanding. CoRR abs/2004.09297 (2020) - [i118]Yi Ren, Jinglin Liu, Xu Tan, Sheng Zhao, Zhou Zhao, Tie-Yan Liu:
A Study of Non-autoregressive Model for Sequence Generation. CoRR abs/2004.10454 (2020) - [i117]Kaitao Song, Hao Sun, Xu Tan, Tao Qin, Jianfeng Lu, Hongzhi Liu, Tie-Yan Liu:
LightPAFF: A Two-Stage Distillation Framework for Pre-training and Fine-tuning. CoRR abs/2004.12817 (2020) - [i116]Wentao Xu, Shun Zheng, Liang He, Bin Shao, Jian Yin, Tie-Yan Liu:
SEEK: Segmented Embedding of Knowledge Graphs. CoRR abs/2005.00856 (2020) - [i115]Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu:
Invertible Image Rescaling. CoRR abs/2005.05650 (2020) - [i114]Zhibing Zhao, Yingce Xia, Tao Qin, Lirong Xia, Tie-Yan Liu:
Dual Learning: Theoretical Study and an Algorithmic Extension. CoRR abs/2005.08238 (2020) - [i113]Yi Ren, Chenxu Hu, Xu Tan, Tao Qin, Sheng Zhao, Zhou Zhao, Tie-Yan Liu:
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech. CoRR abs/2006.04558 (2020) - [i112]Zhenhui Xu, Linyuan Gong, Guolin Ke, Di He, Shuxin Zheng, Liwei Wang, Jiang Bian, Tie-Yan Liu:
MC-BERT: Efficient Language Pre-Training via a Meta Controller. CoRR abs/2006.05744 (2020) - [i111]Chen Zhang, Xu Tan, Yi Ren, Tao Qin, Kejun Zhang, Tie-Yan Liu:
UWSpeech: Speech to Speech Translation for Unwritten Languages. CoRR abs/2006.07926 (2020) - [i110]Yang Fan, Shufang Xie, Yingce Xia, Lijun Wu, Tao Qin, Xiang-Yang Li, Tie-Yan Liu:
Multi-branch Attentive Transformer. CoRR abs/2006.10270 (2020) - [i109]Yaolong Wang, Mingqing Xiao, Chang Liu, Shuxin Zheng, Tie-Yan Liu:
Modeling Lost Information in Lossy Image Compression. CoRR abs/2006.11999 (2020) - [i108]Qi Meng, Shiqi Gong, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu:
Dynamic of Stochastic Gradient Descent with State-Dependent Noise. CoRR abs/2006.13719 (2020) - [i107]Guolin Ke, Di He, Tie-Yan Liu:
Rethinking Positional Encoding in Language Pre-training. CoRR abs/2006.15595 (2020) - [i106]Yi Ren, Xu Tan, Tao Qin, Jian Luan, Zhou Zhao, Tie-Yan Liu:
DeepSinger: Singing Voice Synthesis with Data Mined From the Web. CoRR abs/2007.04590 (2020) - [i105]Yang Fan, Yingce Xia, Lijun Wu, Shufang Xie, Weiqing Liu, Jiang Bian, Tao Qin, Xiang-Yang Li, Tie-Yan Liu:
Learning to Teach with Deep Interactions. CoRR abs/2007.04649 (2020) - [i104]Renqian Luo, Xu Tan, Rui Wang, Tao Qin, Enhong Chen, Tie-Yan Liu:
Neural Architecture Search with GBDT. CoRR abs/2007.04785 (2020) - [i103]Xueqing Wu, Yingce Xia, Lijun Wu, Shufang Xie, Weiqing Liu, Jiang Bian, Tao Qin, Tie-Yan Liu:
Learn to Use Future Information in Simultaneous Translation. CoRR abs/2007.05290 (2020) - [i102]Jinglin Liu, Yi Ren, Xu Tan, Chen Zhang, Tao Qin, Zhou Zhao, Tie-Yan Liu:
Task-Level Curriculum Learning for Non-Autoregressive Neural Machine Translation. CoRR abs/2007.08772 (2020) - [i101]Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
Membership Inference with Privately Augmented Data Endorses the Benign while Suppresses the Adversary. CoRR abs/2007.10567 (2020) - [i100]Chaohui Yu, Jindong Wang, Chang Liu, Tao Qin, Renjun Xu, Wenjie Feng, Yiqiang Chen, Tie-Yan Liu:
Learning to Match Distributions for Domain Adaptation. CoRR abs/2007.10791 (2020) - [i99]Qiyu Wu, Chen Xing, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu:
Taking Notes on the Fly Helps BERT Pre-training. CoRR abs/2008.01466 (2020) - [i98]Jin Xu, Xu Tan, Yi Ren, Tao Qin, Jian Li, Sheng Zhao, Tie-Yan Liu:
LRSpeech: Extremely Low-Resource Speech Synthesis and Recognition. CoRR abs/2008.03687 (2020) - [i97]Yi Ren, Jinzheng He, Xu Tan, Tao Qin, Zhou Zhao, Tie-Yan Liu:
PopMAG: Pop Music Accompaniment Generation. CoRR abs/2008.07703 (2020) - [i96]Jiawei Chen, Xu Tan, Jian Luan, Tao Qin, Tie-Yan Liu:
HiFiSinger: Towards High-Fidelity Neural Singing Voice Synthesis. CoRR abs/2009.01776 (2020) - [i95]Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang:
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training. CoRR abs/2009.03294 (2020) - [i94]Weicong Chen, Xu Tan, Yingce Xia, Tao Qin, Yu Wang, Tie-Yan Liu:
DualLip: A System for Joint Lip Reading and Generation. CoRR abs/2009.05784 (2020) - [i93]Xiao Yang, Weiqing Liu, Dong Zhou, Jiang Bian, Tie-Yan Liu:
Qlib: An AI-oriented Quantitative Investment Platform. CoRR abs/2009.11189 (2020) - [i92]Hao Wang, Jia Zhang, Yingce Xia, Jiang Bian, Chao Zhang, Tie-Yan Liu:
COSEA: Convolutional Code Search with Layer-wise Attention. CoRR abs/2010.09520 (2020) - [i91]Chang Liu, Xinwei Sun, Jindong Wang, Tao Li, Tao Qin, Wei Chen, Tie-Yan Liu:
Learning Causal Semantic Representation for Out-of-Distribution Prediction. CoRR abs/2011.01681 (2020) - [i90]Xinwei Sun, Botong Wu, Chang Liu, Xiangyu Zheng, Wei Chen, Tao Qin, Tie-Yan Liu:
Latent Causal Invariant Model. CoRR abs/2011.02203 (2020) - [i89]Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu:
The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks. CoRR abs/2012.06244 (2020) - [i88]Chen Zhang, Yi Ren, Xu Tan, Jinglin Liu, Kejun Zhang, Tao Qin, Sheng Zhao, Tie-Yan Liu:
DenoiSpeech: Denoising Text to Speech with Frame-Level Noise Modeling. CoRR abs/2012.09547 (2020) - [i87]Wenlei Shi, Xinran Wei, Jia Zhang, Xiaoyuan Ni, Arthur Jiang, Jiang Bian, Tie-Yan Liu:
Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations. CoRR abs/2012.13099 (2020)
2010 – 2019
- 2019
- [j42]Qi Meng, Wei Chen, Yue Wang, Zhi-Ming Ma, Tie-Yan Liu:
Convergence analysis of distributed stochastic gradient descent with shuffling. Neurocomputing 337: 46-57 (2019) - [j41]Li He, Shuxin Zheng, Wei Chen, Zhiming Ma, Tie-Yan Liu:
OptQuant: Distributed training of neural networks with optimized quantization mechanisms. Neurocomputing 340: 233-244 (2019) - [j40]Quanming Yao, James T. Kwok, Taifeng Wang, Tie-Yan Liu:
Large-Scale Low-Rank Matrix Learning with Nonconvex Regularizers. IEEE Trans. Pattern Anal. Mach. Intell. 41(11): 2628-2643 (2019) - [j39]Yijun Wang, Yingce Xia, Li Zhao, Jiang Bian, Tao Qin, Enhong Chen, Tie-Yan Liu:
Semi-Supervised Neural Machine Translation via Marginal Distribution Estimation. IEEE ACM Trans. Audio Speech Lang. Process. 27(10): 1564-1576 (2019) - [j38]Lijun Wu, Xu Tan, Tao Qin, Jianhuang Lai, Tie-Yan Liu:
Beyond Error Propagation: Language Branching Also Affects the Accuracy of Sequence Generation. IEEE ACM Trans. Audio Speech Lang. Process. 27(12): 1868-1879 (2019) - [c183]Junliang Guo, Xu Tan, Di He, Tao Qin, Linli Xu, Tie-Yan Liu:
Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input. AAAI 2019: 3723-3730 - [c182]Guoqing Liu, Li Zhao, Feidiao Yang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu:
Trust Region Evolution Strategies. AAAI 2019: 4352-4359 - [c181]Yiren Wang, Fei Tian, Di He, Tao Qin, ChengXiang Zhai, Tie-Yan Liu:
Non-Autoregressive Machine Translation with Auxiliary Regularization. AAAI 2019: 5377-5384 - [c180]Chang Xu, Weiran Huang, Hongwei Wang, Gang Wang, Tie-Yan Liu:
Modeling Local Dependence in Natural Language with Multi-Channel Recurrent Neural Networks. AAAI 2019: 5525-5532 - [c179]Shuxin Zheng, Qi Meng, Huishuai Zhang, Wei Chen, Nenghai Yu, Tie-Yan Liu:
Capacity Control of ReLU Neural Networks by Basis-Path Norm. AAAI 2019: 5925-5932 - [c178]Yichong Leng, Xu Tan, Tao Qin, Xiang-Yang Li, Tie-Yan Liu:
Unsupervised Pivot Translation for Distant Languages. ACL (1) 2019: 175-183 - [c177]Fei Gao, Jinhua Zhu, Lijun Wu, Yingce Xia, Tao Qin, Xueqi Cheng, Wengang Zhou, Tie-Yan Liu:
Soft Contextual Data Augmentation for Neural Machine Translation. ACL (1) 2019: 5539-5544 - [c176]Lijun Wu, Yiren Wang, Yingce Xia, Fei Tian, Fei Gao, Tao Qin, Jianhuang Lai, Tie-Yan Liu:
Depth Growing for Neural Machine Translation. ACL (1) 2019: 5558-5563 - [c175]Hao Sun, Xu Tan, Jun-Wei Gan, Sheng Zhao, Dongxu Han, Hongzhi Liu, Tao Qin, Tie-Yan Liu:
Knowledge Distillation from Bert in Pre-Training and Fine-Tuning for Polyphone Disambiguation. ASRU 2019: 168-175 - [c174]Xihan Li, Jia Zhang, Jiang Bian, Yunhai Tong, Tie-Yan Liu:
A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics Network. AAMAS 2019: 980-988 - [c173]Xu Tan, Jiale Chen, Di He, Yingce Xia, Tao Qin, Tie-Yan Liu:
Multilingual Neural Machine Translation with Language Clustering. EMNLP/IJCNLP (1) 2019: 963-973 - [c172]Lijun Wu, Yiren Wang, Yingce Xia, Tao Qin, Jianhuang Lai, Tie-Yan Liu:
Exploiting Monolingual Data at Scale for Neural Machine Translation. EMNLP/IJCNLP (1) 2019: 4205-4215 - [c171]Lijun Wu, Jinhua Zhu, Di He, Fei Gao, Tao Qin, Jianhuang Lai, Tie-Yan Liu:
Machine Translation With Weakly Paired Documents. EMNLP/IJCNLP (1) 2019: 4374-4383 - [c170]Zhuohan Li, Zi Lin, Di He, Fei Tian, Tao Qin, Liwei Wang, Tie-Yan Liu:
Hint-Based Training for Non-Autoregressive Machine Translation. EMNLP/IJCNLP (1) 2019: 5707-5712 - [c169]Jun Gao, Di He, Xu Tan, Tao Qin, Liwei Wang, Tie-Yan Liu:
Representation Degeneration Problem in Training Natural Language Generation Models. ICLR (Poster) 2019 - [c168]Qi Meng, Shuxin Zheng, Huishuai Zhang, Wei Chen, Qiwei Ye, Zhi-Ming Ma, Nenghai Yu, Tie-Yan Liu:
G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space. ICLR (Poster) 2019 - [c167]Xu Tan, Yi Ren, Di He, Tao Qin, Zhou Zhao, Tie-Yan Liu:
Multilingual Neural Machine Translation with Knowledge Distillation. ICLR (Poster) 2019 - [c166]Yiren Wang, Yingce Xia, Tianyu He, Fei Tian, Tao Qin, ChengXiang Zhai, Tie-Yan Liu:
Multi-Agent Dual Learning. ICLR (Poster) 2019 - [c165]Linyuan Gong, Di He, Zhuohan Li, Tao Qin, Liwei Wang, Tie-Yan Liu:
Efficient Training of BERT by Progressively Stacking. ICML 2019: 2337-2346 - [c164]Yi Ren, Xu Tan, Tao Qin, Sheng Zhao, Zhou Zhao, Tie-Yan Liu:
Almost Unsupervised Text to Speech and Automatic Speech Recognition. ICML 2019: 5410-5419 - [c163]Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, Tie-Yan Liu:
MASS: Masked Sequence to Sequence Pre-training for Language Generation. ICML 2019: 5926-5936 - [c162]Lijun Zhang, Tie-Yan Liu, Zhi-Hua Zhou:
Adaptive Regret of Convex and Smooth Functions. ICML 2019: 7414-7423 - [c161]Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu:
BN-invariant Sharpness Regularizes the Training Model to Better Generalization. IJCAI 2019: 4164-4170 - [c160]Chang Xu, Tao Qin, Gang Wang, Tie-Yan Liu:
Polygon-Net: A General Framework for Jointly Boosting Multiple Unsupervised Neural Machine Translation Models. IJCAI 2019: 5320-5326 - [c159]Hao Sun, Xu Tan, Jun-Wei Gan, Hongzhi Liu, Sheng Zhao, Tao Qin, Tie-Yan Liu:
Token-Level Ensemble Distillation for Grapheme-to-Phoneme Conversion. INTERSPEECH 2019: 2115-2119 - [c158]Guolin Ke, Zhenhui Xu, Jia Zhang, Jiang Bian, Tie-Yan Liu:
DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks. KDD 2019: 384-394 - [c157]Zhige Li, Derek Yang, Li Zhao, Jiang Bian, Tao Qin, Tie-Yan Liu:
Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding. KDD 2019: 894-902 - [c156]Chi Chen, Li Zhao, Jiang Bian, Chunxiao Xing, Tie-Yan Liu:
Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction. KDD 2019: 2376-2384 - [c155]Yi Ren, Yangjun Ruan, Xu Tan, Tao Qin, Sheng Zhao, Zhou Zhao, Tie-Yan Liu:
FastSpeech: Fast, Robust and Controllable Text to Speech. NeurIPS 2019: 3165-3174 - [c154]Derek Yang, Li Zhao, Zichuan Lin, Tao Qin, Jiang Bian, Tie-Yan Liu:
Fully Parameterized Quantile Function for Distributional Reinforcement Learning. NeurIPS 2019: 6190-6199 - [c153]Zichuan Lin, Li Zhao, Derek Yang, Tao Qin, Tie-Yan Liu, Guangwen Yang:
Distributional Reward Decomposition for Reinforcement Learning. NeurIPS 2019: 6212-6221 - [c152]Yiren Wang, Yingce Xia, Fei Tian, Fei Gao, Tao Qin, ChengXiang Zhai, Tie-Yan Liu:
Neural Machine Translation with Soft Prototype. NeurIPS 2019: 6313-6322 - [c151]Lu Hou, Jinhua Zhu, James T. Kwok, Fei Gao, Tao Qin, Tie-Yan Liu:
Normalization Helps Training of Quantized LSTM. NeurIPS 2019: 7344-7354 - [c150]Yingce Xia, Xu Tan, Fei Tian, Fei Gao, Di He, Weicong Chen, Yang Fan, Linyuan Gong, Yichong Leng, Renqian Luo, Yiren Wang, Lijun Wu, Jinhua Zhu, Tao Qin, Tie-Yan Liu:
Microsoft Research Asia's Systems for WMT19. WMT (2) 2019: 424-433 - [i86]Yiren Wang, Fei Tian, Di He, Tao Qin, ChengXiang Zhai, Tie-Yan Liu:
Non-Autoregressive Machine Translation with Auxiliary Regularization. CoRR abs/1902.10245 (2019) - [i85]Xu Tan, Yi Ren, Di He, Tao Qin, Zhou Zhao, Tie-Yan Liu:
Multilingual Neural Machine Translation with Knowledge Distillation. CoRR abs/1902.10461 (2019) - [i84]Xihan Li, Jia Zhang, Jiang Bian, Yunhai Tong, Tie-Yan Liu:
A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics Network. CoRR abs/1903.00714 (2019) - [i83]Mingyang Yi, Qi Meng, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu:
Positively Scale-Invariant Flatness of ReLU Neural Networks. CoRR abs/1903.02237 (2019) - [i82]Ling Pan, Qingpeng Cai, Qi Meng, Wei Chen, Longbo Huang, Tie-Yan Liu:
Reinforcement Learning with Dynamic Boltzmann Softmax Updates. CoRR abs/1903.05926 (2019) - [i81]Huishuai Zhang, Da Yu, Wei Chen, Tie-Yan Liu:
Training Over-parameterized Deep ResNet Is almost as Easy as Training a Two-layer Network. CoRR abs/1903.07120 (2019) - [i80]Hao Sun, Xu Tan, Jun-Wei Gan, Hongzhi Liu, Sheng Zhao, Tao Qin, Tie-Yan Liu:
Token-Level Ensemble Distillation for Grapheme-to-Phoneme Conversion. CoRR abs/1904.03446 (2019) - [i79]Lijun Zhang, Tie-Yan Liu, Zhi-Hua Zhou:
Adaptive Regret of Convex and Smooth Functions. CoRR abs/1904.11681 (2019) - [i78]Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, Tie-Yan Liu:
MASS: Masked Sequence to Sequence Pre-training for Language Generation. CoRR abs/1905.02450 (2019) - [i77]Yi Ren, Xu Tan, Tao Qin, Sheng Zhao, Zhou Zhao, Tie-Yan Liu:
Almost Unsupervised Text to Speech and Automatic Speech Recognition. CoRR abs/1905.06791 (2019) - [i76]Yi Ren, Yangjun Ruan, Xu Tan, Tao Qin, Sheng Zhao, Zhou Zhao, Tie-Yan Liu:
FastSpeech: Fast, Robust and Controllable Text to Speech. CoRR abs/1905.09263 (2019) - [i75]Jinhua Zhu, Fei Gao, Lijun Wu, Yingce Xia, Tao Qin, Wengang Zhou, Xueqi Cheng, Tie-Yan Liu:
Soft Contextual Data Augmentation for Neural Machine Translation. CoRR abs/1905.10523 (2019) - [i74]Ruihan Yang, Qiwei Ye, Tie-Yan Liu:
Learning Efficient and Effective Exploration Policies with Counterfactual Meta Policy. CoRR abs/1905.11583 (2019) - [i73]Yufei Wang, Qiwei Ye, Tie-Yan Liu:
Beyond Exponentially Discounted Sum: Automatic Learning of Return Function. CoRR abs/1905.11591 (2019) - [i72]Shicong Cen, Huishuai Zhang, Yuejie Chi, Wei Chen, Tie-Yan Liu:
Convergence of Distributed Stochastic Variance Reduced Methods without Sampling Extra Data. CoRR abs/1905.12648 (2019) - [i71]Yichong Leng, Xu Tan, Tao Qin, Xiang-Yang Li, Tie-Yan Liu:
Unsupervised Pivot Translation for Distant Languages. CoRR abs/1906.02461 (2019) - [i70]Yiping Lu, Zhuohan Li, Di He, Zhiqing Sun, Bin Dong, Tao Qin, Liwei Wang, Tie-Yan Liu:
Understanding and Improving Transformer From a Multi-Particle Dynamic System Point of View. CoRR abs/1906.02762 (2019) - [i69]Lijun Wu, Yiren Wang, Yingce Xia, Fei Tian, Fei Gao, Tao Qin, Jianhuang Lai, Tie-Yan Liu:
Depth Growing for Neural Machine Translation. CoRR abs/1907.01968 (2019) - [i68]Zhenhui Xu, Guolin Ke, Jia Zhang, Jiang Bian, Tie-Yan Liu:
Light Multi-segment Activation for Model Compression. CoRR abs/1907.06870 (2019) - [i67]Jun Gao, Di He, Xu Tan, Tao Qin, Liwei Wang, Tie-Yan Liu:
Representation Degeneration Problem in Training Natural Language Generation Models. CoRR abs/1907.12009 (2019) - [i66]Xu Tan, Jiale Chen, Di He, Yingce Xia, Tao Qin, Tie-Yan Liu:
Multilingual Neural Machine Translation with Language Clustering. CoRR abs/1908.09324 (2019) - [i65]Ziyu Liu, Guolin Ke, Jiang Bian, Tie-Yan Liu:
LightMC: A Dynamic and Efficient Multiclass Decomposition Algorithm. CoRR abs/1908.09362 (2019) - [i64]Zhining Liu, Wei Cao, Zhifeng Gao, Jiang Bian, Hechang Chen, Yi Chang, Tie-Yan Liu:
Self-paced Ensemble for Highly Imbalanced Massive Data Classification. CoRR abs/1909.03500 (2019) - [i63]Zhuohan Li, Zi Lin, Di He, Fei Tian, Tao Qin, Liwei Wang, Tie-Yan Liu:
Hint-Based Training for Non-Autoregressive Machine Translation. CoRR abs/1909.06708 (2019) - [i62]Derek Yang, Li Zhao, Zichuan Lin, Tao Qin, Jiang Bian, Tie-Yan Liu:
Fully Parameterized Quantile Function for Distributional Reinforcement Learning. CoRR abs/1911.02140 (2019) - [i61]Zichuan Lin, Li Zhao, Derek Yang, Tao Qin, Guangwen Yang, Tie-Yan Liu:
Distributional Reward Decomposition for Reinforcement Learning. CoRR abs/1911.02166 (2019) - [i60]Yingce Xia, Xu Tan, Fei Tian, Fei Gao, Weicong Chen, Yang Fan, Linyuan Gong, Yichong Leng, Renqian Luo, Yiren Wang, Lijun Wu, Jinhua Zhu, Tao Qin, Tie-Yan Liu:
Microsoft Research Asia's Systems for WMT19. CoRR abs/1911.06191 (2019) - [i59]Junliang Guo, Xu Tan, Linli Xu, Tao Qin, Enhong Chen, Tie-Yan Liu:
Fine-Tuning by Curriculum Learning for Non-Autoregressive Neural Machine Translation. CoRR abs/1911.08717 (2019) - [i58]Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu, Jian Yin:
Gradient Perturbation is Underrated for Differentially Private Convex Optimization. CoRR abs/1911.11363 (2019) - [i57]Xu Tan, Yichong Leng, Jiale Chen, Yi Ren, Tao Qin, Tie-Yan Liu:
A Study of Multilingual Neural Machine Translation. CoRR abs/1912.11625 (2019) - 2018
- [j37]Fei Tian, Tao Qin, Tie-Yan Liu:
Computational pricing in Internet era. Frontiers Comput. Sci. 12(1): 40-54 (2018) - [c149]Yijun Wang, Yingce Xia, Li Zhao, Jiang Bian, Tao Qin, Guiquan Liu, Tie-Yan Liu:
Dual Transfer Learning for Neural Machine Translation with Marginal Distribution Regularization. AAAI 2018: 5553-5560 - [c148]Lijun Wu, Fei Tian, Li Zhao, Jianhuang Lai, Tie-Yan Liu:
Word Attention for Sequence to Sequence Text Understanding. AAAI 2018: 5578-5585 - [c147]Lijun Wu, Yingce Xia, Fei Tian, Li Zhao, Tao Qin, Jianhuang Lai, Tie-Yan Liu:
Adversarial Neural Machine Translation. ACML 2018: 534-549 - [c146]Feidiao Yang, Tiancheng Jin, Tie-Yan Liu, Xiaoming Sun, Jialin Zhang:
Boosting Dynamic Programming with Neural Networks for Solving NP-hard Problems. ACML 2018: 726-739 - [c145]Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu:
Slim-DP: A Multi-Agent System for Communication-Efficient Distributed Deep Learning. AAMAS 2018: 721-729 - [c144]Kaitao Song, Xu Tan, Di He, Jianfeng Lu, Tao Qin, Tie-Yan Liu:
Double Path Networks for Sequence to Sequence Learning. COLING 2018: 3064-3074 - [c143]Jianxin Lin, Yingce Xia, Tao Qin, Zhibo Chen, Tie-Yan Liu:
Conditional Image-to-Image Translation. CVPR 2018: 5524-5532 - [c142]Lijun Wu, Xu Tan, Di He, Fei Tian, Tao Qin, Jianhuang Lai, Tie-Yan Liu:
Beyond Error Propagation in Neural Machine Translation: Characteristics of Language Also Matter. EMNLP 2018: 3602-3611 - [c141]Lijun Wu, Fei Tian, Tao Qin, Jianhuang Lai, Tie-Yan Liu:
A Study of Reinforcement Learning for Neural Machine Translation. EMNLP 2018: 3612-3621 - [c140]Yang Fan, Fei Tian, Tao Qin, Xiang-Yang Li, Tie-Yan Liu:
Learning to Teach. ICLR (Poster) 2018 - [c139]Zhuohan Li, Di He, Fei Tian, Wei Chen, Tao Qin, Liwei Wang, Tie-Yan Liu:
Towards Binary-Valued Gates for Robust LSTM Training. ICML 2018: 3001-3010 - [c138]Yingce Xia, Xu Tan, Fei Tian, Tao Qin, Nenghai Yu, Tie-Yan Liu:
Model-Level Dual Learning. ICML 2018: 5379-5388 - [c137]Li He, Qi Meng, Wei Chen, Zhiming Ma, Tie-Yan Liu:
Differential Equations for Modeling Asynchronous Algorithms. IJCAI 2018: 2220-2226 - [c136]Yi Ding, Weiqing Liu, Jiang Bian, Daoqiang Zhang, Tie-Yan Liu:
Investor-Imitator: A Framework for Trading Knowledge Extraction. KDD 2018: 1310-1319 - [c135]Fei Gao, Lijun Wu, Li Zhao, Tao Qin, Xueqi Cheng, Tie-Yan Liu:
Efficient Sequence Learning with Group Recurrent Networks. NAACL-HLT 2018: 799-808 - [c134]Yanyao Shen, Xu Tan, Di He, Tao Qin, Tie-Yan Liu:
Dense Information Flow for Neural Machine Translation. NAACL-HLT 2018: 1294-1303 - [c133]ChengYue Gong, Di He, Xu Tan, Tao Qin, Liwei Wang, Tie-Yan Liu:
FRAGE: Frequency-Agnostic Word Representation. NeurIPS 2018: 1341-1352 - [c132]Lijun Wu, Fei Tian, Yingce Xia, Yang Fan, Tao Qin, Jian-Huang Lai, Tie-Yan Liu:
Learning to Teach with Dynamic Loss Functions. NeurIPS 2018: 6467-6478 - [c131]Huishuai Zhang, Wei Chen, Tie-Yan Liu:
On the Local Hessian in Back-propagation. NeurIPS 2018: 6521-6531 - [c130]Renqian Luo, Fei Tian, Tao Qin, Enhong Chen, Tie-Yan Liu:
Neural Architecture Optimization. NeurIPS 2018: 7827-7838 - [c129]Tianyu He, Xu Tan, Yingce Xia, Di He, Tao Qin, Zhibo Chen, Tie-Yan Liu:
Layer-Wise Coordination between Encoder and Decoder for Neural Machine Translation. NeurIPS 2018: 7955-7965 - [c128]Chenyan Xiong, Zhengzhong Liu, Jamie Callan, Tie-Yan Liu:
Towards Better Text Understanding and Retrieval through Kernel Entity Salience Modeling. SIGIR 2018: 575-584 - [c127]Ziniu Hu, Weiqing Liu, Jiang Bian, Xuanzhe Liu, Tie-Yan Liu:
Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction. WSDM 2018: 261-269 - [e6]Shichao Zhang, Tie-Yan Liu, Xianxian Li, Jiafeng Guo, Chenliang Li:
Information Retrieval - 24th China Conference, CCIR 2018, Guilin, China, September 27-29, 2018, Proceedings. Lecture Notes in Computer Science 11168, Springer 2018, ISBN 978-3-030-01011-9 [contents] - [e5]Dawei Song, Tie-Yan Liu, Le Sun, Peter Bruza, Massimo Melucci, Fabrizio Sebastiani, Grace Hui Yang:
Proceedings of the 2018 ACM SIGIR International Conference on Theory of Information Retrieval, ICTIR 2018, Tianjin, China, September 14-17, 2018. ACM 2018 [contents] - [i56]Qi Meng, Wei Chen, Shuxin Zheng, Qiwei Ye, Tie-Yan Liu:
Optimizing Neural Networks in the Equivalent Class Space. CoRR abs/1802.03713 (2018) - [i55]Huishuai Zhang, Wei Chen, Tie-Yan Liu:
Train Feedfoward Neural Network with Layer-wise Adaptive Rate via Approximating Back-matching Propagation. CoRR abs/1802.09750 (2018) - [i54]Hany Hassan, Anthony Aue, Chang Chen, Vishal Chowdhary, Jonathan Clark, Christian Federmann, Xuedong Huang, Marcin Junczys-Dowmunt, William Lewis, Mu Li, Shujie Liu, Tie-Yan Liu, Renqian Luo, Arul Menezes, Tao Qin, Frank Seide, Xu Tan, Fei Tian, Lijun Wu, Shuangzhi Wu, Yingce Xia, Dongdong Zhang, Zhirui Zhang, Ming Zhou:
Achieving Human Parity on Automatic Chinese to English News Translation. CoRR abs/1803.05567 (2018) - [i53]Jianxin Lin, Yingce Xia, Tao Qin, Zhibo Chen, Tie-Yan Liu:
Conditional Image-to-Image Translation. CoRR abs/1805.00251 (2018) - [i52]Chenyan Xiong, Zhengzhong Liu, Jamie Callan, Tie-Yan Liu:
Towards Better Text Understanding and Retrieval through Kernel Entity Salience Modeling. CoRR abs/1805.01334 (2018) - [i51]Li He, Qi Meng, Wei Chen, Zhiming Ma, Tie-Yan Liu:
Differential Equations for Modeling Asynchronous Algorithms. CoRR abs/1805.02991 (2018) - [i50]Yang Fan, Fei Tian, Tao Qin, Xiang-Yang Li, Tie-Yan Liu:
Learning to Teach. CoRR abs/1805.03643 (2018) - [i49]Yanyao Shen, Xu Tan, Di He, Tao Qin, Tie-Yan Liu:
Dense Information Flow for Neural Machine Translation. CoRR abs/1806.00722 (2018) - [i48]Zhuohan Li, Di He, Fei Tian, Wei Chen, Tao Qin, Liwei Wang, Tie-Yan Liu:
Towards Binary-Valued Gates for Robust LSTM Training. CoRR abs/1806.02988 (2018) - [i47]Kaitao Song, Xu Tan, Di He, Jianfeng Lu, Tao Qin, Tie-Yan Liu:
Double Path Networks for Sequence to Sequence Learning. CoRR abs/1806.04856 (2018) - [i46]Renqian Luo, Fei Tian, Tao Qin, Tie-Yan Liu:
Neural Architecture Optimization. CoRR abs/1808.07233 (2018) - [i45]Lijun Wu, Fei Tian, Tao Qin, Jianhuang Lai, Tie-Yan Liu:
A Study of Reinforcement Learning for Neural Machine Translation. CoRR abs/1808.08866 (2018) - [i44]Lijun Wu, Xu Tan, Di He, Fei Tian, Tao Qin, Jianhuang Lai, Tie-Yan Liu:
Beyond Error Propagation in Neural Machine Translation: Characteristics of Language Also Matter. CoRR abs/1809.00120 (2018) - [i43]ChengYue Gong, Di He, Xu Tan, Tao Qin, Liwei Wang, Tie-Yan Liu:
FRAGE: Frequency-Agnostic Word Representation. CoRR abs/1809.06858 (2018) - [i42]Shuxin Zheng, Qi Meng, Huishuai Zhang, Wei Chen, Nenghai Yu, Tie-Yan Liu:
Capacity Control of ReLU Neural Networks by Basis-path Norm. CoRR abs/1809.07122 (2018) - [i41]Yue Wang, Qi Meng, Wei Chen, Yuting Liu, Zhiming Ma, Tie-Yan Liu:
Target Transfer Q-Learning and Its Convergence Analysis. CoRR abs/1809.08923 (2018) - [i40]Yue Wang, Wei Chen, Yuting Liu, Zhi-Ming Ma, Tie-Yan Liu:
Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting. CoRR abs/1809.08926 (2018) - [i39]Lijun Wu, Fei Tian, Yingce Xia, Yang Fan, Tao Qin, Jianhuang Lai, Tie-Yan Liu:
Learning to Teach with Dynamic Loss Functions. CoRR abs/1810.12081 (2018) - [i38]Chang Xu, Weiran Huang, Hongwei Wang, Gang Wang, Tie-Yan Liu:
Modeling Local Dependence in Natural Language with Multi-channel Recurrent Neural Networks. CoRR abs/1811.05121 (2018) - [i37]Junliang Guo, Xu Tan, Di He, Tao Qin, Linli Xu, Tie-Yan Liu:
Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input. CoRR abs/1812.09664 (2018) - 2017
- [j36]Yingce Xia, Tao Qin, Wenkui Ding, Haifang Li, Xudong Zhang, Nenghai Yu, Tie-Yan Liu:
Finite budget analysis of multi-armed bandit problems. Neurocomputing 258: 13-29 (2017) - [j35]Geoffrey Holmes, Tie-Yan Liu, Hang Li, Irwin King, Masashi Sugiyama, Zhi-Hua Zhou:
Introduction: special issue of selected papers from ACML 2015. Mach. Learn. 106(4): 459-461 (2017) - [c126]Jiang Rong, Tao Qin, Bo An, Tie-Yan Liu:
Revenue Maximization for Finitely Repeated Ad Auctions. AAAI 2017: 663-669 - [c125]Jia Zhang, Weidong Ma, Tao Qin, Xiaoming Sun, Tie-Yan Liu:
Randomized Mechanisms for Selling Reserved Instances in Cloud Computing. AAAI 2017: 750-757 - [c124]Qi Meng, Wei Chen, Jingcheng Yu, Taifeng Wang, Zhiming Ma, Tie-Yan Liu:
Asynchronous Stochastic Proximal Optimization Algorithms with Variance Reduction. AAAI 2017: 2329-2335 - [c123]Qi Meng, Yue Wang, Wei Chen, Taifeng Wang, Zhiming Ma, Tie-Yan Liu:
Generalization Error Bounds for Optimization Algorithms via Stability. AAAI 2017: 2336-2342 - [c122]Jiang Rong, Tao Qin, Bo An, Tie-Yan Liu:
Pricing Optimization for Selling Reusable Resources. AAMAS 2017: 1719-1721 - [c121]Chang Xu, Tao Qin, Yalong Bai, Gang Wang, Tie-Yan Liu:
Convolutional neural networks for posed and spontaneous expression recognition. ICME 2017: 769-774 - [c120]Yingce Xia, Tao Qin, Wei Chen, Jiang Bian, Nenghai Yu, Tie-Yan Liu:
Dual Supervised Learning. ICML 2017: 3789-3798 - [c119]Shuxin Zheng, Qi Meng, Taifeng Wang, Wei Chen, Nenghai Yu, Zhiming Ma, Tie-Yan Liu:
Asynchronous Stochastic Gradient Descent with Delay Compensation. ICML 2017: 4120-4129 - [c118]Lijun Wu, Li Zhao, Tao Qin, Jianhuang Lai, Tie-Yan Liu:
Sequence Prediction with Unlabeled Data by Reward Function Learning. IJCAI 2017: 3098-3104 - [c117]Yingce Xia, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu:
Dual Inference for Machine Learning. IJCAI 2017: 3112-3118 - [c116]Quanming Yao, James T. Kwok, Fei Gao, Wei Chen, Tie-Yan Liu:
Efficient Inexact Proximal Gradient Algorithm for Nonconvex Problems. IJCAI 2017: 3308-3314 - [c115]Xujin Chen, Xiaodong Hu, Tie-Yan Liu, Weidong Ma, Tao Qin, Pingzhong Tang, Changjun Wang, Bo Zheng:
Efficient Mechanism Design for Online Scheduling (Extended Abstract). IJCAI 2017: 4985-4989 - [c114]Di He, Hanqing Lu, Yingce Xia, Tao Qin, Liwei Wang, Tie-Yan Liu:
Decoding with Value Networks for Neural Machine Translation. NIPS 2017: 178-187 - [c113]Yingce Xia, Fei Tian, Lijun Wu, Jianxin Lin, Tao Qin, Nenghai Yu, Tie-Yan Liu:
Deliberation Networks: Sequence Generation Beyond One-Pass Decoding. NIPS 2017: 1784-1794 - [c112]Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, Tie-Yan Liu:
LightGBM: A Highly Efficient Gradient Boosting Decision Tree. NIPS 2017: 3146-3154 - [c111]Yue Wang, Wei Chen, Yuting Liu, Zhiming Ma, Tie-Yan Liu:
Finite sample analysis of the GTD Policy Evaluation Algorithms in Markov Setting. NIPS 2017: 5504-5513 - [c110]Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu:
Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks. ECML/PKDD (1) 2017: 187-202 - [c109]Yingce Xia, Fei Tian, Tao Qin, Nenghai Yu, Tie-Yan Liu:
Sequence Generation with Target Attention. ECML/PKDD (1) 2017: 816-831 - [c108]Chenyan Xiong, Jamie Callan, Tie-Yan Liu:
Word-Entity Duet Representations for Document Ranking. SIGIR 2017: 763-772 - [c107]Di He, Aadharsh Kannan, Tie-Yan Liu, R. Preston McAfee, Tao Qin, Justin M. Rao:
Scale Effects in Web Search. WINE 2017: 294-310 - [c106]Tie-Yan Liu, Wei Chen, Taifeng Wang:
Distributed Machine Learning: Foundations, Trends, and Practices. WWW (Companion Volume) 2017: 913-915 - [i36]Yang Fan, Fei Tian, Tao Qin, Jiang Bian, Tie-Yan Liu:
Learning What Data to Learn. CoRR abs/1702.08635 (2017) - [i35]Lijun Wu, Yingce Xia, Li Zhao, Fei Tian, Tao Qin, Jianhuang Lai, Tie-Yan Liu:
Adversarial Neural Machine Translation. CoRR abs/1704.06933 (2017) - [i34]Chang Xu, Tao Qin, Gang Wang, Tie-Yan Liu:
Reinforcement Learning for Learning Rate Control. CoRR abs/1705.11159 (2017) - [i33]Chenyan Xiong, Jamie Callan, Tie-Yan Liu:
Word-Entity Duet Representations for Document Ranking. CoRR abs/1706.06636 (2017) - [i32]Yingce Xia, Tao Qin, Wei Chen, Jiang Bian, Nenghai Yu, Tie-Yan Liu:
Dual Supervised Learning. CoRR abs/1707.00415 (2017) - [i31]Quanming Yao, James T. Kwok, Taifeng Wang, Tie-Yan Liu:
Large-Scale Low-Rank Matrix Learning with Nonconvex Regularizers. CoRR abs/1708.00146 (2017) - [i30]Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu:
Slim-DP: A Light Communication Data Parallelism for DNN. CoRR abs/1709.09393 (2017) - [i29]Qi Meng, Wei Chen, Yue Wang, Zhiming Ma, Tie-Yan Liu:
Convergence Analysis of Distributed Stochastic Gradient Descent with Shuffling. CoRR abs/1709.10432 (2017) - 2016
- [j34]Xujin Chen, Xiaodong Hu, Tie-Yan Liu, Weidong Ma, Tao Qin, Pingzhong Tang, Changjun Wang, Bo Zheng:
Efficient Mechanism Design for Online Scheduling. J. Artif. Intell. Res. 56: 429-461 (2016) - [j33]Fei Tian, Bin Gao, Enhong Chen, Tie-Yan Liu:
Learning Better Word Embedding by Asymmetric Low-Rank Projection of Knowledge Graph. J. Comput. Sci. Technol. 31(3): 624-634 (2016) - [j32]Chang Xu, Gang Wang, Xiaoguang Liu, Dongdong Guo, Tie-Yan Liu:
Health Status Assessment and Failure Prediction for Hard Drives with Recurrent Neural Networks. IEEE Trans. Computers 65(11): 3502-3508 (2016) - [j31]Wei Wei, Bin Gao, Tie-Yan Liu, Taifeng Wang, Guohui Li, Hang Li:
A Ranking Approach on Large-Scale Graph With Multidimensional Heterogeneous Information. IEEE Trans. Cybern. 46(4): 930-944 (2016) - [j30]Shuaiqiang Wang, Shanshan Huang, Tie-Yan Liu, Jun Ma, Zhumin Chen, Jari Veijalainen:
Ranking-Oriented Collaborative Filtering: A Listwise Approach. ACM Trans. Inf. Syst. 35(2): 10:1-10:28 (2016) - [c105]Shizhao Sun, Wei Chen, Liwei Wang, Xiaoguang Liu, Tie-Yan Liu:
On the Depth of Deep Neural Networks: A Theoretical View. AAAI 2016: 2066-2072 - [c104]Tie-Yan Liu, Weidong Ma, Tao Qin, Pingzhong Tang, Guang Yang, Bo Zheng:
Online Non-Preemptive Story Scheduling in Web Advertising. AAMAS 2016: 269-277 - [c103]Yingce Xia, Tao Qin, Nenghai Yu, Tie-Yan Liu:
Best Action Selection in a Stochastic Environment. AAMAS 2016: 758-766 - [c102]Jiang Rong, Tao Qin, Bo An, Tie-Yan Liu:
Optimal Sample Size for Adword Auctions: (Extended Abstract). AAMAS 2016: 1459-1460 - [c101]Jiang Rong, Tao Qin, Bo An, Tie-Yan Liu:
Modeling Bounded Rationality for Sponsored Search Auctions. ECAI 2016: 515-523 - [c100]Huazheng Wang, Fei Tian, Bin Gao, Chengjieren Zhu, Jiang Bian, Tie-Yan Liu:
Solving Verbal Questions in IQ Test by Knowledge-Powered Word Embedding. EMNLP 2016: 541-550 - [c99]Chenyan Xiong, Jamie Callan, Tie-Yan Liu:
Bag-of-Entities Representation for Ranking. ICTIR 2016: 181-184 - [c98]Qi Meng, Wei Chen, Jingcheng Yu, Taifeng Wang, Zhiming Ma, Tie-Yan Liu:
Asynchronous Accelerated Stochastic Gradient Descent. IJCAI 2016: 1853-1859 - [c97]Yingce Xia, Tao Qin, Weidong Ma, Nenghai Yu, Tie-Yan Liu:
Budgeted Multi-Armed Bandits with Multiple Plays. IJCAI 2016: 2210-2216 - [c96]Di He, Yingce Xia, Tao Qin, Liwei Wang, Nenghai Yu, Tie-Yan Liu, Wei-Ying Ma:
Dual Learning for Machine Translation. NIPS 2016: 820-828 - [c95]Qi Meng, Guolin Ke, Taifeng Wang, Wei Chen, Qiwei Ye, Zhiming Ma, Tie-Yan Liu:
A Communication-Efficient Parallel Algorithm for Decision Tree. NIPS 2016: 1271-1279 - [c94]Xiang Li, Tao Qin, Jian Yang, Tie-Yan Liu:
LightRNN: Memory and Computation-Efficient Recurrent Neural Networks. NIPS 2016: 4385-4393 - [i28]Fei Tian, Bin Gao, Di He, Tie-Yan Liu:
Sentence Level Recurrent Topic Model: Letting Topics Speak for Themselves. CoRR abs/1604.02038 (2016) - [i27]Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu:
Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks. CoRR abs/1606.00575 (2016) - [i26]Shuxin Zheng, Qi Meng, Taifeng Wang, Wei Chen, Nenghai Yu, Zhiming Ma, Tie-Yan Liu:
Asynchronous Stochastic Gradient Descent with Delay Compensation for Distributed Deep Learning. CoRR abs/1609.08326 (2016) - [i25]Qi Meng, Yue Wang, Wei Chen, Taifeng Wang, Zhiming Ma, Tie-Yan Liu:
Generalization Error Bounds for Optimization Algorithms via Stability. CoRR abs/1609.08397 (2016) - [i24]Qi Meng, Wei Chen, Jingcheng Yu, Taifeng Wang, Zhiming Ma, Tie-Yan Liu:
Asynchronous Stochastic Proximal Optimization Algorithms with Variance Reduction. CoRR abs/1609.08435 (2016) - [i23]Xiang Li, Tao Qin, Jian Yang, Tie-Yan Liu:
LightRNN: Memory and Computation-Efficient Recurrent Neural Networks. CoRR abs/1610.09893 (2016) - [i22]Yingce Xia, Di He, Tao Qin, Liwei Wang, Nenghai Yu, Tie-Yan Liu, Wei-Ying Ma:
Dual Learning for Machine Translation. CoRR abs/1611.00179 (2016) - [i21]Qi Meng, Guolin Ke, Taifeng Wang, Wei Chen, Qiwei Ye, Zhiming Ma, Tie-Yan Liu:
A Communication-Efficient Parallel Algorithm for Decision Tree. CoRR abs/1611.01276 (2016) - [i20]Jia Zhang, Weidong Ma, Tao Qin, Xiaoming Sun, Tie-Yan Liu:
Randomized Mechanisms for Selling Reserved Instances in Cloud. CoRR abs/1611.07379 (2016) - 2015
- [j29]Qing Cui, Feng-Shan Bai, Bin Gao, Tie-Yan Liu:
Global Optimization for Advertisement Selection in Sponsored Search. J. Comput. Sci. Technol. 30(2): 295-310 (2015) - [j28]Qing Cui, Bin Gao, Jiang Bian, Siyu Qiu, Hanjun Dai, Tie-Yan Liu:
KNET: A General Framework for Learning Word Embedding Using Morphological Knowledge. ACM Trans. Inf. Syst. 34(1): 4:1-4:25 (2015) - [c93]Haifang Li, Fei Tian, Wei Chen, Tao Qin, Zhiming Ma, Tie-Yan Liu:
Generalization Analysis for Game-Theoretic Machine Learning. AAAI 2015: 2089-2095 - [c92]Tie-Yan Liu, Wei Chen, Tao Qin:
Mechanism Learning with Mechanism Induced Data. AAAI 2015: 4037-4041 - [c91]Geoffrey Holmes, Tie-Yan Liu:
Preface. ACML 2015: 7 - [c90]Binyi Chen, Tao Qin, Tie-Yan Liu:
Mechanism Design for Daily Deals. AAMAS 2015: 327-335 - [c89]Bolei Xu, Tao Qin, Guoping Qiu, Tie-Yan Liu:
Competitive Pricing for Cloud Computing in an Evolutionary Market. AAMAS 2015: 1755-1756 - [c88]Changjun Wang, Weidong Ma, Tao Qin, Feidiao Yang, Tie-Yan Liu, Xujin Chen, Xiao-Dong Hu:
New Mechanism for Reservation in Cloud Computing. AAMAS 2015: 1765-1766 - [c87]Bolei Xu, Tao Qin, Guoping Qiu, Tie-Yan Liu:
Optimal Pricing for the Competitive and Evolutionary Cloud Market. IJCAI 2015: 139-145 - [c86]Changjun Wang, Weidong Ma, Tao Qin, Xujin Chen, Xiaodong Hu, Tie-Yan Liu:
Selling Reserved Instances in Cloud Computing. IJCAI 2015: 224-231 - [c85]Yingce Xia, Haifang Li, Tao Qin, Nenghai Yu, Tie-Yan Liu:
Thompson Sampling for Budgeted Multi-Armed Bandits. IJCAI 2015: 3960-3966 - [c84]Shanshan Huang, Shuaiqiang Wang, Tie-Yan Liu, Jun Ma, Zhumin Chen, Jari Veijalainen:
Listwise Collaborative Filtering. SIGIR 2015: 343-352 - [c83]Jinhui Yuan, Fei Gao, Qirong Ho, Wei Dai, Jinliang Wei, Xun Zheng, Eric Poe Xing, Tie-Yan Liu, Wei-Ying Ma:
LightLDA: Big Topic Models on Modest Computer Clusters. WWW 2015: 1351-1361 - [e4]Tie-Yan Liu, Christie Napa Scollon, Wenwu Zhu:
Social Informatics - 7th International Conference, SocInfo 2015, Beijing, China, December 9-12, 2015, Proceedings. Lecture Notes in Computer Science 9471, Springer 2015, ISBN 978-3-319-27432-4 [contents] - [i19]Yingce Xia, Haifang Li, Tao Qin, Nenghai Yu, Tie-Yan Liu:
Thompson Sampling for Budgeted Multi-armed Bandits. CoRR abs/1505.00146 (2015) - [i18]Fei Tian, Bin Gao, Enhong Chen, Tie-Yan Liu:
Learning Better Word Embedding by Asymmetric Low-Rank Projection of Knowledge Graph. CoRR abs/1505.04891 (2015) - [i17]Huazheng Wang, Bin Gao, Jiang Bian, Fei Tian, Tie-Yan Liu:
Solving Verbal Comprehension Questions in IQ Test by Knowledge-Powered Word Embedding. CoRR abs/1505.07909 (2015) - [i16]Shizhao Sun, Wei Chen, Liwei Wang, Tie-Yan Liu:
Large Margin Deep Neural Networks: Theory and Algorithms. CoRR abs/1506.05232 (2015) - 2014
- [j27]Ying Zhang, Weinan Zhang, Bin Gao, Xiaojie Yuan, Tie-Yan Liu:
Bid keyword suggestion in sponsored search based on competitiveness and relevance. Inf. Process. Manag. 50(4): 508-523 (2014) - [j26]Sungchul Kim, Tao Qin, Tie-Yan Liu, Hwanjo Yu:
Advertiser-centric approach to understand user click behavior in sponsored search. Inf. Sci. 276: 242-254 (2014) - [j25]Tao Qin, Wei Chen, Tie-Yan Liu:
Sponsored Search Auctions: Recent Advances and Future Directions. ACM Trans. Intell. Syst. Technol. 5(4): 60:1-60:34 (2014) - [c82]Yingce Xia, Tao Qin, Nenghai Yu, Tie-Yan Liu:
Incentivizing High-Quality Content from Heterogeneous Users: On the Existence of Nash Equilibrium. AAAI 2014: 819-825 - [c81]Fei Tian, Bin Gao, Qing Cui, Enhong Chen, Tie-Yan Liu:
Learning Deep Representations for Graph Clustering. AAAI 2014: 1293-1299 - [c80]Fei Tian, Haifang Li, Wei Chen, Tao Qin, Enhong Chen, Tie-Yan Liu:
Agent Behavior Prediction and Its Generalization Analysis. AAAI 2014: 1300-1306 - [c79]Yuyu Zhang, Hanjun Dai, Chang Xu, Jun Feng, Taifeng Wang, Jiang Bian, Bin Wang, Tie-Yan Liu:
Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks. AAAI 2014: 1369-1375 - [c78]Weidong Ma, Tao Wu, Tao Qin, Tie-Yan Liu:
Generalized second price auctions with value externalities. AAMAS 2014: 1457-1458 - [c77]Chang Xu, Yalong Bai, Jiang Bian, Bin Gao, Gang Wang, Xiaoguang Liu, Tie-Yan Liu:
RC-NET: A General Framework for Incorporating Knowledge into Word Representations. CIKM 2014: 1219-1228 - [c76]Siyu Qiu, Qing Cui, Jiang Bian, Bin Gao, Tie-Yan Liu:
Co-learning of Word Representations and Morpheme Representations. COLING 2014: 141-150 - [c75]Fei Tian, Hanjun Dai, Jiang Bian, Bin Gao, Rui Zhang, Enhong Chen, Tie-Yan Liu:
A Probabilistic Model for Learning Multi-Prototype Word Embeddings. COLING 2014: 151-160 - [c74]Jiang Bian, Bin Gao, Tie-Yan Liu:
Knowledge-Powered Deep Learning for Word Embedding. ECML/PKDD (1) 2014: 132-148 - [c73]Wei Chen, Di He, Tie-Yan Liu, Tao Qin, Yixin Tao, Liwei Wang:
Generalized second price auction with probabilistic broad match. EC 2014: 39-56 - [c72]Jun Feng, Jiang Bian, Taifeng Wang, Wei Chen, Xiaoyan Zhu, Tie-Yan Liu:
Sampling dilemma: towards effective data sampling for click prediction in sponsored search. WSDM 2014: 103-112 - [e3]Tie-Yan Liu, Qi Qi, Yinyu Ye:
Web and Internet Economics - 10th International Conference, WINE 2014, Beijing, China, December 14-17, 2014. Proceedings. Lecture Notes in Computer Science 8877, Springer 2014, ISBN 978-3-319-13128-3 [contents] - [i15]Weidong Ma, Bo Zheng, Tao Qin, Pingzhong Tang, Tie-Yan Liu:
Online Mechanism Design for Cloud Computing. CoRR abs/1403.1896 (2014) - [i14]Wei Chen, Di He, Tie-Yan Liu, Tao Qin, Yixin Tao, Liwei Wang:
Generalized Second Price Auction with Probabilistic Broad Match. CoRR abs/1404.3828 (2014) - [i13]Fei Tian, Haifang Li, Wei Chen, Tao Qin, Enhong Chen, Tie-Yan Liu:
Agent Behavior Prediction and Its Generalization Analysis. CoRR abs/1404.4960 (2014) - [i12]Yingce Xia, Tao Qin, Nenghai Yu, Tie-Yan Liu:
Incentivizing High-quality Content from Heterogeneous Users: On the Existence of Nash Equilibrium. CoRR abs/1404.5155 (2014) - [i11]Yuyu Zhang, Hanjun Dai, Chang Xu, Jun Feng, Taifeng Wang, Jiang Bian, Bin Wang, Tie-Yan Liu:
Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks. CoRR abs/1404.5772 (2014) - [i10]Di He, Wei Chen, Liwei Wang, Tie-Yan Liu:
A Game-theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search. CoRR abs/1406.0728 (2014) - [i9]Bin Gao, Jiang Bian, Tie-Yan Liu:
WordRep: A Benchmark for Research on Learning Word Representations. CoRR abs/1407.1640 (2014) - [i8]Qing Cui, Bin Gao, Jiang Bian, Siyu Qiu, Tie-Yan Liu:
Learning Effective Word Embedding using Morphological Word Similarity. CoRR abs/1407.1687 (2014) - [i7]Haifang Li, Fei Tian, Wei Chen, Tao Qin, Tie-Yan Liu:
Generalization Analysis for Game-Theoretic Machine Learning. CoRR abs/1410.3341 (2014) - [i6]Jinhui Yuan, Fei Gao, Qirong Ho, Wei Dai, Jinliang Wei, Xun Zheng, Eric P. Xing, Tie-Yan Liu, Wei-Ying Ma:
LightLDA: Big Topic Models on Modest Compute Clusters. CoRR abs/1412.1576 (2014) - 2013
- [j24]Di He, Wei Chen, Liwei Wang, Tie-Yan Liu:
Online learning for auction mechanism in bandit setting. Decis. Support Syst. 56: 379-386 (2013) - [c71]Wenkui Ding, Tao Qin, Xu-Dong Zhang, Tie-Yan Liu:
Multi-Armed Bandit with Budget Constraint and Variable Costs. AAAI 2013: 232-238 - [c70]Yining Wang, Liwei Wang, Yuanzhi Li, Di He, Tie-Yan Liu:
A Theoretical Analysis of NDCG Type Ranking Measures. COLT 2013: 25-54 - [c69]Di He, Wei Chen, Liwei Wang, Tie-Yan Liu:
A Game-Theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search. IJCAI 2013: 206-212 - [c68]Taifeng Wang, Jiang Bian, Shusen Liu, Yuyu Zhang, Tie-Yan Liu:
Psychological advertising: exploring user psychology for click prediction in sponsored search. KDD 2013: 563-571 - [c67]Min Xu, Tao Qin, Tie-Yan Liu:
Estimation Bias in Multi-Armed Bandit Algorithms for Search Advertising. NIPS 2013: 2400-2408 - [c66]Bin Gao, Jun Yan, Dou Shen, Tie-Yan Liu:
Internet advertising: theory and practice. SIGIR 2013: 1135 - [c65]Weihao Kong, Jian Li, Tie-Yan Liu, Tao Qin:
Optimal Allocation for Chunked-Reward Advertising. WINE 2013: 291-304 - [c64]Haifeng Xu, Bin Gao, Diyi Yang, Tie-Yan Liu:
Predicting advertiser bidding behaviors in sponsored search by rationality modeling. WWW 2013: 1433-1444 - [e2]Rafael E. Banchs, Fabrizio Silvestri, Tie-Yan Liu, Min Zhang, Sheng Gao, Jun Lang:
Information Retrieval Technology - 9th Asia Information Retrieval Societies Conference, AIRS 2013, Singapore, December 9-11, 2013. Proceedings. Lecture Notes in Computer Science 8281, Springer 2013, ISBN 978-3-642-45067-9 [contents] - [i5]Yining Wang, Liwei Wang, Yuanzhi Li, Di He, Tie-Yan Liu, Wei Chen:
A Theoretical Analysis of NDCG Type Ranking Measures. CoRR abs/1304.6480 (2013) - [i4]Wenkui Ding, Tao Wu, Tao Qin, Tie-Yan Liu:
Pure Price of Anarchy for Generalized Second Price Auction. CoRR abs/1305.5404 (2013) - [i3]Weihao Kong, Jian Li, Tao Qin, Tie-Yan Liu:
Revenue Optimization for Group-Buying Websites. CoRR abs/1305.5946 (2013) - [i2]Tao Qin, Tie-Yan Liu:
Introducing LETOR 4.0 Datasets. CoRR abs/1306.2597 (2013) - [i1]Binyi Chen, Tao Qin, Tie-Yan Liu:
$K$-anonymous Signaling Scheme. CoRR abs/1311.6638 (2013) - 2012
- [j23]Xiubo Geng, Tao Qin, Tie-Yan Liu, Xueqi Cheng:
A noise-tolerant graphical model for ranking. Inf. Process. Manag. 48(2): 374-383 (2012) - [c63]Changhao Jiang, Min Zhang, Bin Gao, Tie-Yan Liu:
A Study on Potential Head Advertisers in Sponsored Search. AIRS 2012: 174-186 - [c62]Konstantin Salomatin, Tie-Yan Liu, Yiming Yang:
A unified optimization framework for auction and guaranteed delivery in online advertising. CIKM 2012: 2005-2009 - [c61]Weinan Zhang, Ying Zhang, Bin Gao, Yong Yu, Xiaojie Yuan, Tie-Yan Liu:
Joint optimization of bid and budget allocation in sponsored search. KDD 2012: 1177-1185 - [c60]Yanyan Lan, Jiafeng Guo, Xueqi Cheng, Tie-Yan Liu:
Statistical Consistency of Ranking Methods in A Rank-Differentiable Probability Space. NIPS 2012: 1241-1249 - [c59]Bin Gao, Taifeng Wang, Tie-Yan Liu:
Large-scale graph mining and learning for information retrieval. SIGIR 2012: 1194-1195 - [c58]Lei Yao, Wei Chen, Tie-Yan Liu:
Convergence Analysis for Weighted Joint Strategy Fictitious Play in Generalized Second Price Auction. WINE 2012: 489-495 - [c57]Chenyan Xiong, Taifeng Wang, Wenkui Ding, Yidong Shen, Tie-Yan Liu:
Relational click prediction for sponsored search. WSDM 2012: 493-502 - 2011
- [b1]Tie-Yan Liu:
Learning to Rank for Information Retrieval. Springer 2011, ISBN 978-3-642-14266-6, pp. I-XVII, 1-285 - [j22]Xiubo Geng, Tao Qin, Tie-Yan Liu, Xueqi Cheng, Hang Li:
Selecting optimal training data for learning to rank. Inf. Process. Manag. 47(5): 730-741 (2011) - [j21]Bin Gao, Tie-Yan Liu, Yuting Liu, Taifeng Wang, Zhiming Ma, Hang Li:
Page importance computation based on Markov processes. Inf. Retr. 14(5): 488-514 (2011) - [j20]Wei-Ying Ma, Tie-Yan Liu, Ji-Rong Wen, Zheng Chen, Zaiqing Nie, Xing Xie, Hang Li, Haixun Wang, Yu Zheng:
A conversation with MSRA researchers. SIGKDD Explor. 13(2): 82-84 (2011) - [c56]Sungchul Kim, Tao Qin, Hwanjo Yu, Tie-Yan Liu:
Advertiser-centric approach to understand user click behavior in sponsored search. CIKM 2011: 2121-2124 - [c55]Bin Gao, Tie-Yan Liu, Wei Wei, Taifeng Wang, Hang Li:
Semi-supervised ranking on very large graphs with rich metadata. KDD 2011: 96-104 - [c54]Zhicong Cheng, Bin Gao, Congkai Sun, Yanbing Jiang, Tie-Yan Liu:
Let web spammers expose themselves. WSDM 2011: 525-534 - [c53]Bin Gao, Taifeng Wang, Tie-Yan Liu:
Ranking on large-scale graphs with rich metadata. WWW (Companion Volume) 2011: 285-286 - [c52]Olivier Chapelle, Yi Chang, Tie-Yan Liu:
Future directions in learning to rank. Yahoo! Learning to Rank Challenge 2011: 91-100 - [e1]Olivier Chapelle, Yi Chang, Tie-Yan Liu:
Proceedings of the Yahoo! Learning to Rank Challenge, held at ICML 2010, Haifa, Israel, June 25, 2010. JMLR Proceedings 14, JMLR.org 2011 [contents] - 2010
- [j19]Yuting Liu, Tie-Yan Liu, Bin Gao, Zhiming Ma, Hang Li:
A framework to compute page importance based on user behaviors. Inf. Retr. 13(1): 22-45 (2010) - [j18]Tie-Yan Liu, Thorsten Joachims, Hang Li, Chengxiang Zhai:
Introduction to special issue on learning to rank for information retrieval. Inf. Retr. 13(3): 197-200 (2010) - [j17]Tao Qin, Tie-Yan Liu, Jun Xu, Hang Li:
LETOR: A benchmark collection for research on learning to rank for information retrieval. Inf. Retr. 13(4): 346-374 (2010) - [j16]Tao Qin, Tie-Yan Liu, Hang Li:
A general approximation framework for direct optimization of information retrieval measures. Inf. Retr. 13(4): 375-397 (2010) - [j15]Yin He, Tie-Yan Liu:
Tendency correlation analysis for direct optimization of evaluation measures in information retrieval. Inf. Retr. 13(6): 657-688 (2010) - [c51]Wei Chen, Tie-Yan Liu, Zhiming Ma:
Two-Layer Generalization Analysis for Ranking Using Rademacher Average. NIPS 2010: 370-378 - [c50]Tao Qin, Xiubo Geng, Tie-Yan Liu:
A New Probabilistic Model for Rank Aggregation. NIPS 2010: 1948-1956 - [c49]Tie-Yan Liu:
Learning to rank for information retrieval. SIGIR 2010: 904 - [c48]Jiang Bian, Tie-Yan Liu, Tao Qin, Hongyuan Zha:
Ranking with query-dependent loss for web search. WSDM 2010: 141-150 - [c47]Zhicong Cheng, Bin Gao, Tie-Yan Liu:
Actively predicting diverse search intent from user browsing behaviors. WWW 2010: 221-230
2000 – 2009
- 2009
- [j14]Tie-Yan Liu:
Learning to Rank for Information Retrieval. Found. Trends Inf. Retr. 3(3): 225-331 (2009) - [j13]Hang Li, Tie-Yan Liu, ChengXiang Zhai:
Learning to rank for information retrieval (LR4IR 2009). SIGIR Forum 43(2): 41-45 (2009) - [c46]Bin Gao, Tie-Yan Liu, Zhiming Ma, Taifeng Wang, Hang Li:
A general markov framework for page importance computation. CIKM 2009: 1835-1838 - [c45]Yanyan Lan, Tie-Yan Liu, Zhiming Ma, Hang Li:
Generalization analysis of listwise learning-to-rank algorithms. ICML 2009: 577-584 - [c44]Wei Chen, Tie-Yan Liu, Yanyan Lan, Zhiming Ma, Hang Li:
Ranking Measures and Loss Functions in Learning to Rank. NIPS 2009: 315-323 - [c43]Fen Xia, Tie-Yan Liu, Hang Li:
Statistical Consistency of Top-k Ranking. NIPS 2009: 2098-2106 - 2008
- [j12]Tao Qin, Xu-Dong Zhang, Ming-Feng Tsai, De-Sheng Wang, Tie-Yan Liu, Hang Li:
Query-level loss functions for information retrieval. Inf. Process. Manag. 44(2): 838-855 (2008) - [j11]Tao Qin, Xu-Dong Zhang, Tie-Yan Liu, De-Sheng Wang, Wei-Ying Ma, Hong-Jiang Zhang:
An active feedback framework for image retrieval. Pattern Recognit. Lett. 29(5): 637-646 (2008) - [j10]Hang Li, Tie-Yan Liu, ChengXiang Zhai:
Learning to rank for information retrieval (LR4IR 2008). SIGIR Forum 42(2): 76-79 (2008) - [c42]Yanyan Lan, Tie-Yan Liu, Tao Qin, Zhiming Ma, Hang Li:
Query-level stability and generalization in learning to rank. ICML 2008: 512-519 - [c41]Fen Xia, Tie-Yan Liu, Jue Wang, Wensheng Zhang, Hang Li:
Listwise approach to learning to rank: theory and algorithm. ICML 2008: 1192-1199 - [c40]Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang, Hang Li:
Global Ranking Using Continuous Conditional Random Fields. NIPS 2008: 1281-1288 - [c39]Jun Xu, Tie-Yan Liu, Min Lu, Hang Li, Wei-Ying Ma:
Directly optimizing evaluation measures in learning to rank. SIGIR 2008: 107-114 - [c38]Xiubo Geng, Tie-Yan Liu, Tao Qin, Andrew Arnold, Hang Li, Heung-Yeung Shum:
Query dependent ranking using K-nearest neighbor. SIGIR 2008: 115-122 - [c37]Yuting Liu, Bin Gao, Tie-Yan Liu, Ying Zhang, Zhiming Ma, Shuyuan He, Hang Li:
BrowseRank: letting web users vote for page importance. SIGIR 2008: 451-458 - [c36]Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang, Wen-Ying Xiong, Hang Li:
Learning to rank relational objects and its application to web search. WWW 2008: 407-416 - 2007
- [j9]Ying Bao, Guang Feng, Tie-Yan Liu, Zhiming Ma, Ying Wang:
Ranking Websites: A Probabilistic View. Internet Math. 3(3): 295-320 (2007) - [j8]Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, Guang Feng, De-Sheng Wang, Wei-Ying Ma:
Topic distillation via sub-site retrieval. Inf. Process. Manag. 43(2): 445-460 (2007) - [j7]Thorsten Joachims, Hang Li, Tie-Yan Liu, ChengXiang Zhai:
Learning to rank for information retrieval (LR4IR 2007). SIGIR Forum 41(2): 58-62 (2007) - [c35]Lei Yang, Lei Qi, Yan-Ping Zhao, Bin Gao, Tie-Yan Liu:
Link analysis using time series of web graphs. CIKM 2007: 1011-1014 - [c34]Tie-Yan Liu, Huai-Yuan Yang, Xin Zheng, Tao Qin, Wei-Ying Ma:
Fast Large-Scale Spectral Clustering by Sequential Shrinkage Optimization. ECIR 2007: 319-330 - [c33]Li Zhang, Tao Qin, Tie-Yan Liu, Ying Bao, Hang Li:
N -Step PageRank for Web Search. ECIR 2007: 653-660 - [c32]Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, Hang Li:
Learning to rank: from pairwise approach to listwise approach. ICML 2007: 129-136 - [c31]Tao Qin, Xu-Dong Zhang, De-Sheng Wang, Tie-Yan Liu, Wei Lai, Hang Li:
Ranking with multiple hyperplanes. SIGIR 2007: 279-286 - [c30]Ming-Feng Tsai, Tie-Yan Liu, Tao Qin, Hsin-Hsi Chen, Wei-Ying Ma:
FRank: a ranking method with fidelity loss. SIGIR 2007: 383-390 - [c29]Xiubo Geng, Tie-Yan Liu, Tao Qin, Hang Li:
Feature selection for ranking. SIGIR 2007: 407-414 - [c28]Yuting Liu, Tie-Yan Liu, Tao Qin, Zhiming Ma, Hang Li:
Supervised rank aggregation. WWW 2007: 481-490 - 2006
- [c27]Bo Chen, Bin Gao, Tie-Yan Liu, Yu-Fu Chen, Wei-Ying Ma:
Fast Spectral Clustering of Data Using Sequential Matrix Compression. ECML 2006: 590-597 - [c26]Bin Gao, Tie-Yan Liu, Wei-Ying Ma:
Star-Structured High-Order Heterogeneous Data Co-clustering Based on Consistent Information Theory. ICDM 2006: 880-884 - [c25]Guoyang Shen, Bin Gao, Tie-Yan Liu, Guang Feng, Shiji Song, Hang Li:
Detecting Link Spam Using Temporal Information. ICDM 2006: 1049-1053 - [c24]Qiankun Zhao, Tie-Yan Liu, Sourav S. Bhowmick, Wei-Ying Ma:
Event detection from evolution of click-through data. KDD 2006: 484-493 - [c23]Huai-Yuan Yang, Tie-Yan Liu, Li Gao, Wei-Ying Ma:
Heterogeneous Information Integration in Hierarchical Text Classification. PAKDD 2006: 240-249 - [c22]Guang Feng, Tie-Yan Liu, Xudong Zhang, Wei-Ying Ma:
Level-Biased Statistics in the Hierarchical Structure of the Web. PAKDD 2006: 313-322 - [c21]Guang Feng, Tie-Yan Liu, Ying Wang, Ying Bao, Zhiming Ma, Xu-Dong Zhang, Wei-Ying Ma:
AggregateRank: bringing order to web sites. SIGIR 2006: 75-82 - [c20]Yunbo Cao, Jun Xu, Tie-Yan Liu, Hang Li, Yalou Huang, Hsiao-Wuen Hon:
Adapting ranking SVM to document retrieval. SIGIR 2006: 186-193 - [c19]Qiankun Zhao, Steven C. H. Hoi, Tie-Yan Liu, Sourav S. Bhowmick, Michael R. Lyu, Wei-Ying Ma:
Time-dependent semantic similarity measure of queries using historical click-through data. WWW 2006: 543-552 - 2005
- [j6]Tie-Yan Liu, Yiming Yang, Hao Wan, Hua-Jun Zeng, Zheng Chen, Wei-Ying Ma:
Support vector machines classification with a very large-scale taxonomy. SIGKDD Explor. 7(1): 36-43 (2005) - [j5]Bin Gao, Tie-Yan Liu, Guang Feng, Tao Qin, QianSheng Cheng, Wei-Ying Ma:
Hierarchical Taxonomy Preparation for Text Categorization Using Consistent Bipartite Spectral Graph Copartitioning. IEEE Trans. Knowl. Data Eng. 17(9): 1263-1273 (2005) - [c18]Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, Guang Feng, Wei-Ying Ma:
Subsite Retrieval: A Novel Concept for Topic Distillation. AIRS 2005: 388-400 - [c17]Hui-Min Yan, Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, Guang Feng, Wei-Ying Ma:
Calculating Webpage Importance with Site Structure Constraints. AIRS 2005: 546-551 - [c16]Guang Feng, Tie-Yan Liu, Xu-Dong Zhang, Tao Qin, Bin Gao, Wei-Ying Ma:
Level-Based Link Analysis. APWeb 2005: 183-194 - [c15]Bin Gao, Tie-Yan Liu, Xin Zheng, QianSheng Cheng, Wei-Ying Ma:
Consistent bipartite graph co-partitioning for star-structured high-order heterogeneous data co-clustering. KDD 2005: 41-50 - [c14]Ying Liu, Tao Qin, Tie-Yan Liu, Lei Zhang, Wei-Ying Ma:
Similarity space projection for web image search and annotation. Multimedia Information Retrieval 2005: 49-56 - [c13]Bin Gao, Tie-Yan Liu, Tao Qin, Xin Zheng, QianSheng Cheng, Wei-Ying Ma:
Web image clustering by consistent utilization of visual features and surrounding texts. ACM Multimedia 2005: 112-121 - [c12]Tie-Yan Liu, Wei-Ying Ma, HongJiang Zhang:
Effective Feature Extraction for Play Detection in American Football Video. MMM 2005: 164-171 - [c11]Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, Wei-Ying Ma, HongJiang Zhang:
Subspace Clustering and Label Propagation for Active Feedback in Image Retrieval. MMM 2005: 172-179 - [c10]Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, Zheng Chen, Wei-Ying Ma:
A study of relevance propagation for web search. SIGIR 2005: 408-415 - [c9]Tie-Yan Liu, Hao Wan, Wei-Ying Ma:
An Editor Labeling Model for Training Set Expansion in Web Categorization. Web Intelligence 2005: 165-171 - [c8]Tie-Yan Liu, Wei-Ying Ma:
Webpage Importance Analysis Using Conditional Markov Random Walk. Web Intelligence 2005: 515-521 - [c7]Tie-Yan Liu, Yiming Yang, Hao Wan, Qian Zhou, Bin Gao, Hua-Jun Zeng, Zheng Chen, Wei-Ying Ma:
An experimental study on large-scale web categorization. WWW (Special interest tracks and posters) 2005: 1106-1107 - [c6]Tie-Yan Liu, Hao Wan, Tao Qin, Zheng Chen, Yong Ren, Wei-Ying Ma:
Site abstraction for rare category classification in large-scale web directory. WWW (Special interest tracks and posters) 2005: 1108-1109 - 2004
- [j4]Tie-Yan Liu, Kwok-Tung Lo, Xu-Dong Zhang, Jian Feng:
A new cut detection algorithm with constant false-alarm ratio for video segmentation. J. Vis. Commun. Image Represent. 15(2): 132-144 (2004) - [j3]Tie-Yan Liu, Xudong Zhang, Jian Feng, Kwok-Tung Lo:
Shot reconstruction degree: a novel criterion for key frame selection. Pattern Recognit. Lett. 25(12): 1451-1457 (2004) - [c5]Tie-Yan Liu, Tao Qin, HongJiang Zhang:
Time-constraint boost for tv commercials detection. ICIP 2004: 1617-1620 - [c4]Bin Gao, Tie-Yan Liu, QianSheng Cheng, Wei-Ying Ma:
A Linear Approximation Based Method for Noise-Robust and Illumination-Invariant Image Change Detection. PCM (3) 2004: 95-102 - [c3]Ruihua Song, Ji-Rong Wen, Shuming Shi, Guomao Xin, Tie-Yan Liu, Tao Qin, Xin Zheng, Jiyu Zhang, Gui-Rong Xue, Wei-Ying Ma:
Microsoft Research Asia at Web Track and Terabyte Track of TREC 2004. TREC 2004 - 2003
- [j2]Xu-Dong Zhang, Tie-Yan Liu, Kwok-Tung Lo, Jian Feng:
Dynamic selection and effective compression of key frames for video abstraction. Pattern Recognit. Lett. 24(9-10): 1523-1532 (2003) - [j1]Tie-Yan Liu, Kwok-Tung Lo, Jian Feng, Xudong Zhang:
Frame interpolation scheme using inertia motion prediction. Signal Process. Image Commun. 18(3): 221-229 (2003) - 2002
- [c2]Tie-Yan Liu, Xudong Zhang, Linwei Shan, Yingning Peng:
Constant false-alarm ratio processing for video cut detection. ICIP (1) 2002: 121-124 - 2001
- [c1]Jian Feng, Tie-Yan Liu, Kwok-Tung Lo, Xu-Dong Zhang:
Adaptive motion tracking for fast block motion estimation. ISCAS (5) 2001: 219-222
Coauthor Index
[j74] [j71] [j70] [c306] [c293] [c285] [c283] [i225] [i217] [c276] [c272] [i213] [i212] [i211] [i208] [i197] [j48] [c252] [c247] [c246] [c245] [c227] [c226] [c205] [i174] [i165] [i139] [i133] [i126] [i125] [c203] [c197] [c196] [i115] [i112] [i105] [i103] [i93] [i92] [i87] [j39] [c182] [c174] [c158] [c157] [c156] [c154] [i84] [i68] [i65] [i64] [i62] [c149] [c145] [c136] [c127] [c120] [c117] [c110] [i36] [i32] [i30] [c100] [i27] [j28] [i17] [c79] [c77] [c76] [c75] [c74] [c72] [i11] [i9] [i8] [c68] [c48]
[c301] [j65] [j56] [c275] [c270] [c269] [c268] [c263] [c258] [c254] [i205] [i201] [i194] [i187] [c251] [c234] [c230] [c228] [c218] [c215] [c213] [c210] [c206] [i176] [i170] [i158] [i157] [i156] [i153] [i152] [i149] [i148] [i143] [i132] [i130] [i128] [j46] [j43] [c192] [i108] [i101] [i91] [i90] [i89] [j42] [j41] [c179] [c168] [c161] [i83] [i82] [i81] [i72] [i58] [c145] [c139] [c137] [c131] [i56] [i55] [i51] [i48] [i42] [i41] [i40] [c124] [c123] [c120] [c119] [c116] [c112] [c111] [c110] [c106] [i32] [i30] [i29] [c105] [c98] [c95] [i27] [i26] [i25] [i24] [i21] [c93] [c92] [i16] [j25] [c80] [c73] [c72] [i14] [i13] [i10] [i7] [j24] [c69] [i5] [c58] [c51] [c44]
[c304] [c300] [i230] [i226] [c293] [c291] [c279] [c275] [c256] [i213] [i209] [i204] [i200] [i184] [c244] [c239] [c236] [c232] [c231] [c221] [c211] [c208] [i173] [i172] [i169] [i161] [i158] [i155] [i150] [c197] [c195] [c193] [i124] [i123] [i115] [i112] [i107] [i99] [i95] [c183] [c181] [c173] [c171] [c170] [c169] [c167] [c165] [c150] [i86] [i85] [i70] [i67] [i66] [i63] [c144] [c142] [c139] [c134] [c133] [c129] [i49] [i48] [i47] [i44] [i43] [i37] [c114] [c107] [c96] [i28] [i22] [c73] [i14] [i10] [j24] [c70] [c69] [i5]
Jian-Huang Lai
aka: Jianhuang Lai
aka: Jianhuang Lai
Zhiming Ma
aka: Zhi-Ming Ma
aka: Zhi-Ming Ma
[j77] [j72] [c301] [j65] [c298] [c289] [c288] [i222] [i221] [c270] [c268] [c254] [i205] [i196] [i187] [c230] [c222] [c215] [c210] [c206] [i164] [i157] [i156] [i153] [i149] [i132] [i130] [i108] [i89] [j42] [c179] [c168] [i83] [i82] [c137] [i56] [i51] [i42] [i41] [c124] [c123] [c119] [c112] [i29] [c98] [c95] [i26] [i25] [i24] [i21]
[i233] [j73] [j72] [c306] [c302] [c299] [i228] [i227] [j68] [j67] [j63] [j62] [c297] [c296] [c295] [c294] [c292] [c290] [c289] [c287] [c286] [c284] [c282] [i225] [i224] [i223] [i220] [i219] [i216] [j59] [j58] [j57] [j55] [j52] [c278] [c277] [c274] [c273] [c271] [c270] [c267] [c266] [c265] [c264] [c262] [c261] [c260] [c259] [c258] [c257] [c253] [i215] [i214] [i210] [i206] [i203] [i202] [i201] [i199] [i195] [i193] [i192] [i191] [i190] [i188] [i186] [i185] [i182] [i181] [i180] [i178] [i177] [j48] [j47] [c250] [c249] [c248] [c243] [c242] [c241] [c240] [c238] [c237] [c235] [c233] [c229] [c226] [c225] [c224] [c223] [c222] [c220] [c219] [c218] [c216] [c215] [c213] [c212] [c207] [i175] [i171] [i168] [i167] [i166] [i164] [i163] [i162] [i160] [i159] [i154] [i153] [i151] [i149] [i147] [i146] [i145] [i144] [i142] [i141] [i140] [i138] [i137] [i136] [i134] [i131] [i129] [j45] [c204] [c202] [c200] [c198] [c195] [c194] [c191] [c190] [c189] [c188] [c187] [c186] [c185] [c184] [i123] [i122] [i121] [i119] [i117] [i114] [i113] [i111] [i110] [i106] [i105] [i104] [i103] [i102] [i100] [i98] [i97] [i96] [i94] [i91] [i90] [i88] [j39] [j38] [c183] [c182] [c181] [c178] [c177] [c176] [c175] [c173] [c172] [c171] [c170] [c169] [c167] [c166] [c165] [c164] [c163] [c160] [c159] [c157] [c155] [c154] [c153] [c152] [c151] [c150] [i86] [i85] [i80] [i78] [i77] [i76] [i75] [i71] [i70] [i69] [i67] [i66] [i63] [i62] [i61] [i60] [i59] [i57] [j37] [c149] [c147] [c144] [c143] [c142] [c141] [c140] [c139] [c138] [c135] [c134] [c133] [c132] [c130] [c129] [i54] [i53] [i50] [i49] [i48] [i47] [i46] [i45] [i44] [i43] [i39] [i37] [j36] [c126] [c125] [c122] [c121] [c120] [c118] [c117] [c115] [c114] [c113] [c109] [c107] [i36] [i35] [i34] [i32] [j34] [c104] [c103] [c102] [c101] [c97] [c96] [c94] [i23] [i22] [i20] [c93] [c92] [c90] [c89] [c88] [c87] [c86] [c85] [i19] [j26] [j25] [c82] [c80] [c78] [c73] [i15] [i14] [i13] [i12] [i7] [c71] [c67] [c65] [i4] [i3] [i2] [i1] [j23] [j22] [c56] [j17] [j16] [c50] [c48] [j12] [j11] [c42] [c40] [c38] [c36] [j8] [c34] [c33] [c32] [c31] [c30] [c29] [c28] [j5] [c18] [c17] [c16] [c14] [c13] [c11] [c10] [c6] [c5] [c3]
[j73] [c306] [c302] [c297] [c294] [i225] [i219] [c280] [c278] [c274] [c270] [c266] [c265] [c264] [c261] [c260] [c257] [c253] [i210] [i206] [i202] [i199] [i193] [i192] [i188] [i186] [i181] [i178] [c250] [c249] [c248] [c243] [c242] [c241] [c240] [c238] [c237] [c225] [c224] [c223] [c216] [c212] [i175] [i168] [i163] [i162] [i159] [i154] [i153] [i147] [i144] [i142] [i141] [i140] [i138] [i136] [c202] [c201] [c200] [c191] [c190] [c189] [c188] [c187] [c185] [c184] [i122] [i119] [i118] [i117] [i113] [i111] [i106] [i104] [i102] [i98] [i97] [i96] [i94] [i88] [j38] [c183] [c178] [c175] [c173] [c169] [c167] [c164] [c163] [c159] [c155] [c150] [i85] [i80] [i78] [i77] [i76] [i71] [i67] [i66] [i60] [i59] [i57] [c144] [c142] [c138] [c134] [c133] [c129] [i54] [i49] [i47] [i44] [i43] [i37]
[i233] [j72] [i227] [j68] [j67] [j65] [j63] [j62] [c296] [c295] [c292] [c290] [c289] [c286] [c284] [c282] [i223] [i220] [i216] [j58] [j57] [j55] [j54] [j52] [c273] [c262] [i215] [i212] [i211] [i203] [i195] [i190] [i185] [i180] [c233] [c229] [c222] [c215] [i167] [i164] [i156] [i149] [i137] [i129] [c204] [c195] [c194] [i123] [i110] [i105] [i103] [j38] [c177] [c176] [c172] [c171] [c150] [i75] [i69] [i60] [c148] [c147] [c142] [c141] [c135] [c132] [i54] [i45] [i44] [i39] [c118] [c113] [i35]
[i233] [j68] [j67] [j63] [c295] [c292] [c289] [c287] [c286] [c284] [c282] [i224] [i223] [i220] [i216] [j59] [j58] [j57] [j52] [c273] [c262] [i215] [i195] [i190] [i185] [i182] [i180] [j47] [c233] [c229] [c222] [c209] [i167] [i164] [i151] [i137] [i133] [i129] [i125] [j45] [c204] [c198] [c195] [c194] [c187] [i123] [i114] [i110] [i105] [i103] [i94] [i92] [j39] [c177] [c176] [c173] [c172] [c166] [c152] [c150] [i75] [i69] [i66] [i60] [c149] [c147] [c143] [c138] [c132] [c129] [i54] [i53] [i39] [j36] [c120] [c117] [c114] [c113] [c109] [i35] [i32] [c103] [c97] [c96] [i22] [c85] [i19] [c82] [i12]
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