Google
Google Scholar
Semantic Scholar
MS Academic
CiteSeerX
ORCIDTie-Yan Liu
Person information
- affiliation: Microsoft Research
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2021
[j47]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)- [i124]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) - 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] - [i123]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) - [i122]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) - [i121]Renqian Luo, Xu Tan, Rui Wang, Tao Qin, Enhong Chen, Tie-Yan Liu:
Semi-Supervised Neural Architecture Search. CoRR abs/2002.10389 (2020) - [i120]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) - [i119]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) - [i118]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) - [i117]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) - [i116]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) - [i115]Wentao Xu, Shun Zheng, Liang He, Bin Shao, Jian Yin, Tie-Yan Liu:
SEEK: Segmented Embedding of Knowledge Graphs. CoRR abs/2005.00856 (2020) - [i114]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) - [i113]Zhibing Zhao, Yingce Xia, Tao Qin, Lirong Xia, Tie-Yan Liu:
Dual Learning: Theoretical Study and an Algorithmic Extension. CoRR abs/2005.08238 (2020) - [i112]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) - [i111]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) - [i110]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) - [i109]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) - [i108]Yaolong Wang, Mingqing Xiao, Chang Liu, Shuxin Zheng, Tie-Yan Liu:
Modeling Lost Information in Lossy Image Compression. CoRR abs/2006.11999 (2020) - [i107]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) - [i106]Guolin Ke, Di He, Tie-Yan Liu:
Rethinking Positional Encoding in Language Pre-training. CoRR abs/2006.15595 (2020) - [i105]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) - [i104]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) - [i103]Renqian Luo, Xu Tan, Rui Wang, Tao Qin, Enhong Chen, Tie-Yan Liu:
Neural Architecture Search with GBDT. CoRR abs/2007.04785 (2020) - [i102]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) - [i101]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) - [i100]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) - [i99]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) - [i98]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) - [i97]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) - [i96]Yi Ren, Jinzheng He, Xu Tan, Tao Qin, Zhou Zhao, Tie-Yan Liu:
PopMAG: Pop Music Accompaniment Generation. CoRR abs/2008.07703 (2020) - [i95]Jiawei Chen, Xu Tan, Jian Luan, Tao Qin, Tie-Yan Liu:
HiFiSinger: Towards High-Fidelity Neural Singing Voice Synthesis. CoRR abs/2009.01776 (2020) - [i94]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) - [i93]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) - [i92]Xiao Yang, Weiqing Liu, Dong Zhou, Jiang Bian, Tie-Yan Liu:
Qlib: An AI-oriented Quantitative Investment Platform. CoRR abs/2009.11189 (2020) - [i91]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) - [i90]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) - [i89]Xinwei Sun, Botong Wu, Chang Liu, Xiangyu Zheng, Wei Chen, Tao Qin, Tie-Yan Liu:
Latent Causal Invariant Model. CoRR abs/2011.02203 (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]