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2020 – today
- 2025
[j47]Ruiyu Li, Peilin Zhao, Guangxia Li, Zhiqiang Xu, Xuewei Li:
Online parallel multi-task relationship learning via alternating direction method of multipliers. Neurocomputing 611: 128702 (2025)- 2024
- [j46]Yiqiang Yi
, Xu Wan, Kangfei Zhao, Le Ou-Yang, Peilin Zhao:
Equivariant Line Graph Neural Network for Protein-Ligand Binding Affinity Prediction. IEEE J. Biomed. Health Informatics 28(7): 4336-4347 (2024) - [j45]Shibo Feng, Chunyan Miao, Ke Xu, Jiaxiang Wu, Pengcheng Wu, Yang Zhang, Peilin Zhao:
Multi-Scale Attention Flow for Probabilistic Time Series Forecasting. IEEE Trans. Knowl. Data Eng. 36(5): 2056-2068 (2024) - [c139]Shibo Feng, Chunyan Miao, Zhong Zhang, Peilin Zhao:
Latent Diffusion Transformer for Probabilistic Time Series Forecasting. AAAI 2024: 11979-11987 - [c138]Liang Chen, Yatao Bian, Yang Deng, Deng Cai, Shuaiyi Li, Peilin Zhao, Kam-Fai Wong:
WatME: Towards Lossless Watermarking Through Lexical Redundancy. ACL (1) 2024: 9166-9180 - [c137]Zixuan Liu, Liu Liu, Xueqian Wang, Peilin Zhao:
DFWLayer: Differentiable Frank-Wolfe Optimization Layer. Tiny Papers @ ICLR 2024 - [c136]Yang Liu, Jiashun Cheng, Haihong Zhao, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li, Yu Rong:
SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases. ICLR 2024 - [c135]Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng:
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations. ICLR 2024 - [c134]Zhipeng Zhou, Liu Liu, Peilin Zhao, Wei Gong:
Pareto Deep Long-Tailed Recognition: A Conflict-Averse Solution. ICLR 2024 - [c133]Shuaicheng Niu, Chunyan Miao, Guohao Chen, Pengcheng Wu, Peilin Zhao:
Test-Time Model Adaptation with Only Forward Passes. ICML 2024 - [c132]Yichen Wu, Hong Wang, Peilin Zhao, Yefeng Zheng, Ying Wei, Long-Kai Huang:
Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations via Pareto Optimization. ICML 2024 - [c131]Ziqiao Meng, Liang Zeng, Zixing Song, Tingyang Xu, Peilin Zhao, Irwin King:
Towards Geometric Normalization Techniques in SE(3) Equivariant Graph Neural Networks for Physical Dynamics Simulations. IJCAI 2024: 5981-5989 - [c130]Jiaye Lin, Shuang Peng, Zhong Zhang, Peilin Zhao:
TLRec: A Transfer Learning Framework to Enhance Large Language Models for Sequential Recommendation Tasks. RecSys 2024: 1119-1124 - [i105]Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng:
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations. CoRR abs/2402.03139 (2024) - [i104]Haoyu Wang, Guozheng Ma, Ziqiao Meng, Zeyu Qin, Li Shen, Zhong Zhang, Bingzhe Wu, Liu Liu, Yatao Bian, Tingyang Xu, Xueqian Wang, Peilin Zhao:
Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping. CoRR abs/2402.07610 (2024) - [i103]Huan Ma, Yan Zhu, Changqing Zhang, Peilin Zhao, Baoyuan Wu, Long-Kai Huang, Qinghua Hu, Bingzhe Wu:
Invariant Test-Time Adaptation for Vision-Language Model Generalization. CoRR abs/2403.00376 (2024) - [i102]Mingkui Tan, Guohao Chen, Jiaxiang Wu, Yifan Zhang, Yaofo Chen, Peilin Zhao, Shuaicheng Niu:
Uncertainty-Calibrated Test-Time Model Adaptation without Forgetting. CoRR abs/2403.11491 (2024) - [i101]Shuaicheng Niu, Chunyan Miao, Guohao Chen, Pengcheng Wu, Peilin Zhao:
Test-Time Model Adaptation with Only Forward Passes. CoRR abs/2404.01650 (2024) - [i100]Dezhong Yao, Sanmu Li, Yutong Dai, Zhiqiang Xu, Shengshan Hu, Peilin Zhao, Lichao Sun:
Variational Bayes for Federated Continual Learning. CoRR abs/2405.14291 (2024) - [i99]Zhicheng Chen, Xi Xiao, Ke Xu, Zhong Zhang, Yu Rong, Qing Li, Guojun Gan, Zhiqiang Xu, Peilin Zhao:
MGCP: A Multi-Grained Correlation based Prediction Network for Multivariate Time Series. CoRR abs/2405.19661 (2024) - [i98]Fushuo Huo, Wenchao Xu, Zhong Zhang, Haozhao Wang, Zhicheng Chen, Peilin Zhao:
Self-Introspective Decoding: Alleviating Hallucinations for Large Vision-Language Models. CoRR abs/2408.02032 (2024) - [i97]Haoyu Wang, Bingzhe Wu, Yatao Bian, Yongzhe Chang, Xueqian Wang, Peilin Zhao:
Probing the Safety Response Boundary of Large Language Models via Unsafe Decoding Path Generation. CoRR abs/2408.10668 (2024) - 2023
- [j44]Zhifeng Bao, Panagiotis Bouros, Reynold Cheng, Byron Choi, Anton Dignös, Wei Ding, Yixiang Fang, Boyang Han, Jilin Hu, Arijit Khan, Wenqing Lin, Xuemin Lin, Cheng Long, Nikos Mamoulis, Jian Pei, Matthias Renz, Shashi Shekhar, Jieming Shi, Eleni Tzirita Zacharatou, Sibo Wang, Xiao Wang, Xue Wang, Raymond Chi-Wing Wong, Da Yan, Xifeng Yan, Bin Yang, Dezhong Yao, Ce Zhang, Peilin Zhao, Rong Zhu:
A Summary of ICDE 2022 Research Session Panels. IEEE Data Eng. Bull. 46(4): 4-17 (2023) - [j43]Xuguang Duan, Xin Wang, Peilin Zhao, Guangyao Shen, Wenwu Zhu:
DeepLogic: Joint Learning of Neural Perception and Logical Reasoning. IEEE Trans. Pattern Anal. Mach. Intell. 45(4): 4321-4334 (2023) - [j42]Wendi Wu, Zongren Li, Yawei Zhao, Chen Yu, Peilin Zhao, Ji Liu, Kunlun He:
Decentralized Online Learning: Take Benefits from Others' Data without Sharing Your Own to Track Global Trend. ACM Trans. Intell. Syst. Technol. 14(1): 13:1-13:22 (2023) - [j41]Zixuan Liu, Liu Liu, Bingzhe Wu, Lanqing Li, Xueqian Wang, Bo Yuan, Peilin Zhao:
Dynamics Adapted Imitation Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c129]Ziqi Gao, Yifan Niu, Jiashun Cheng, Jianheng Tang, Lanqing Li, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li:
Handling Missing Data via Max-Entropy Regularized Graph Autoencoder. AAAI 2023: 7651-7659 - [c128]Yuanfeng Ji, Lu Zhang, Jiaxiang Wu, Bingzhe Wu, Lanqing Li, Long-Kai Huang, Tingyang Xu, Yu Rong, Jie Ren, Ding Xue, Houtim Lai, Wei Liu, Junzhou Huang, Shuigeng Zhou, Ping Luo, Peilin Zhao, Yatao Bian:
DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery - a Focus on Affinity Prediction Problems with Noise Annotations. AAAI 2023: 8023-8031 - [c127]Liang Zeng, Lanqing Li, Ziqi Gao, Peilin Zhao, Jian Li:
ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification. AAAI 2023: 11138-11146 - [c126]Qichao Wang, Huan Ma, Wentao Wei, Hangyu Li, Changqing Zhang, Peilin Zhao, Binwen Zhao, Bo Hu, Shu Zhang, Bingzhe Wu, Liang Chen:
Attention Paper: How Generative AI Reshapes Digital Shadow Industry? ACM TUR-C 2023: 143-144 - [c125]Kangfei Zhao, Yu Rong, Biaobin Jiang, Jianheng Tang, Hengtong Zhang, Jeffrey Xu Yu, Peilin Zhao:
Geometric Graph Learning for Protein Mutation Effect Prediction. CIKM 2023: 3412-3422 - [c124]Yong Guo, Yaofo Chen, Yin Zheng, Qi Chen, Peilin Zhao, Junzhou Huang, Jian Chen, Mingkui Tan:
Pareto-aware Neural Architecture Generation for Diverse Computational Budgets. CVPR Workshops 2023: 2248-2258 - [c123]Zhipeng Zhou, Lanqing Li, Peilin Zhao, Pheng-Ann Heng, Wei Gong:
Class-Conditional Sharpness-Aware Minimization for Deep Long-Tailed Recognition. CVPR 2023: 3499-3509 - [c122]Deng-Bao Wang, Lanqing Li, Peilin Zhao, Pheng-Ann Heng, Min-Ling Zhang:
On the Pitfall of Mixup for Uncertainty Calibration. CVPR 2023: 7609-7618 - [c121]Yifan Zhang, Peilin Zhao, Qingyao Wu, Bin Li, Junzhou Huang, Mingkui Tan:
Cost-Sensitive Portfolio Selection via Deep Reinforcement Learning (Extended Abstract). ICDE 2023: 3771-3772 - [c120]Wanjin Feng, Hailong Shi, Peilin Zhao, Xingyu Gao:
Mixtron: Bandit Online Multiclass Prediction with Implicit Feedback. ICDM 2023: 1004-1012 - [c119]Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Bingzhe Wu, Yonggang Zhang, Kaili Ma, Han Yang, Peilin Zhao, Bo Han, James Cheng:
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization. ICLR 2023 - [c118]Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Zhiquan Wen, Yaofo Chen, Peilin Zhao, Mingkui Tan:
Towards Stable Test-time Adaptation in Dynamic Wild World. ICLR 2023 - [c117]Fu-Yun Wang, Da-Wei Zhou, Liu Liu, Han-Jia Ye, Yatao Bian, De-Chuan Zhan, Peilin Zhao:
BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion. ICLR 2023 - [c116]Songtao Liu, Zhengkai Tu, Minkai Xu, Zuobai Zhang, Lu Lin, Rex Ying, Jian Tang, Peilin Zhao, Dinghao Wu:
FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic Planning. ICML 2023: 22028-22041 - [c115]Ziqiao Meng, Peilin Zhao, Yang Yu, Irwin King:
Doubly Stochastic Graph-based Non-autoregressive Reaction Prediction. IJCAI 2023: 4064-4072 - [c114]Ziqiao Meng, Peilin Zhao, Yang Yu, Irwin King:
A Unified View of Deep Learning for Reaction and Retrosynthesis Prediction: Current Status and Future Challenges. IJCAI 2023: 6723-6731 - [c113]Zeyu Cao, Zhipeng Liang, Bingzhe Wu, Shu Zhang, Hangyu Li, Ouyang Wen, Yu Rong, Peilin Zhao:
Privacy Matters: Vertical Federated Linear Contextual Bandits for Privacy Protected Recommendation. KDD 2023: 154-166 - [c112]Long-Kai Huang, Peilin Zhao, Junzhou Huang, Sinno Jialin Pan:
Retaining Beneficial Information from Detrimental Data for Neural Network Repair. NeurIPS 2023 - [c111]Huan Ma, Changqing Zhang, Yatao Bian, Lemao Liu, Zhirui Zhang, Peilin Zhao, Shu Zhang, Huazhu Fu, Qinghua Hu, Bingzhe Wu:
Fairness-guided Few-shot Prompting for Large Language Models. NeurIPS 2023 - [c110]Jianheng Tang, Fengrui Hua, Ziqi Gao, Peilin Zhao, Jia Li:
GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection. NeurIPS 2023 - [c109]Zerun Lin, Yuhan Zhang, Lixin Duan, Le Ou-Yang, Peilin Zhao:
MoVAE: A Variational AutoEncoder for Molecular Graph Generation. SDM 2023: 514-522 - [c108]Ziqiao Meng, Yaoman Li, Peilin Zhao, Yang Yu, Irwin King:
Meta-Learning with Motif-based Task Augmentation for Few-Shot Molecular Property Prediction. SDM 2023: 811-819 - [c107]Hanwen Liu, Peilin Zhao, Tingyang Xu, Yatao Bian, Junzhou Huang, Yuesheng Zhu, Yadong Mu:
Curriculum Graph Poisoning. WWW 2023: 2011-2021 - [i96]Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Zhiquan Wen, Yaofo Chen, Peilin Zhao, Mingkui Tan:
Towards Stable Test-Time Adaptation in Dynamic Wild World. CoRR abs/2302.12400 (2023) - [i95]Ziniu Li, Ke Xu, Liu Liu, Lanqing Li, Deheng Ye, Peilin Zhao:
Deploying Offline Reinforcement Learning with Human Feedback. CoRR abs/2303.07046 (2023) - [i94]Huan Ma, Changqing Zhang, Yatao Bian, Lemao Liu, Zhirui Zhang, Peilin Zhao, Shu Zhang, Huazhu Fu, Qinghua Hu, Bingzhe Wu:
Fairness-guided Few-shot Prompting for Large Language Models. CoRR abs/2303.13217 (2023) - [i93]Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Qinghua Hu, Bingzhe Wu, Changqing Zhang, Jianhua Yao:
Reweighted Mixup for Subpopulation Shift. CoRR abs/2304.04148 (2023) - [i92]Yuanfeng Ji, Yatao Bian, Guoji Fu, Peilin Zhao, Ping Luo:
SyNDock: N Rigid Protein Docking via Learnable Group Synchronization. CoRR abs/2305.15156 (2023) - [i91]Qichao Wang, Huan Ma, Wentao Wei, Hangyu Li, Liang Chen, Peilin Zhao, Binwen Zhao, Bo Hu, Shu Zhang, Zibin Zheng, Bingzhe Wu:
Attention Paper: How Generative AI Reshapes Digital Shadow Industry? CoRR abs/2305.18346 (2023) - [i90]Ziqiao Meng, Peilin Zhao, Yang Yu, Irwin King:
Doubly Stochastic Graph-based Non-autoregressive Reaction Prediction. CoRR abs/2306.06119 (2023) - [i89]Jianheng Tang, Fengrui Hua, Ziqi Gao, Peilin Zhao, Jia Li:
GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection. CoRR abs/2306.12251 (2023) - [i88]Ziqiao Meng, Peilin Zhao, Yang Yu, Irwin King:
A Unified View of Deep Learning for Reaction and Retrosynthesis Prediction: Current Status and Future Challenges. CoRR abs/2306.15890 (2023) - [i87]Peng Tang, Zhiqiang Xu, Pengfei Wei, Xiaobin Hu, Peilin Zhao, Xin Cao, Chunlai Zhou, Tobias Lasser:
SR-R2KAC: Improving Single Image Defocus Deblurring. CoRR abs/2307.16242 (2023) - [i86]Zixuan Liu, Liu Liu, Xueqian Wang, Peilin Zhao:
Differentiable Frank-Wolfe Optimization Layer. CoRR abs/2308.10806 (2023) - [i85]Yang Liu, Jiashun Cheng, Haihong Zhao, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li, Yu Rong:
Physics-Inspired Neural Graph ODE for Long-term Dynamical Simulation. CoRR abs/2308.13212 (2023) - [i84]Haoyu Wang, Guozheng Ma, Cong Yu, Ning Gui, Linrui Zhang, Zhiqi Huang, Suwei Ma, Yongzhe Chang, Sen Zhang, Li Shen, Xueqian Wang, Peilin Zhao, Dacheng Tao:
Are Large Language Models Really Robust to Word-Level Perturbations? CoRR abs/2309.11166 (2023) - [i83]Huan Ma, Changqing Zhang, Huazhu Fu, Peilin Zhao, Bingzhe Wu:
Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning. CoRR abs/2310.03400 (2023) - [i82]Yiqiang Yi, Xu Wan, Yatao Bian, Le Ou-Yang, Peilin Zhao:
ETDock: A Novel Equivariant Transformer for Protein-Ligand Docking. CoRR abs/2310.08061 (2023) - [i81]Yihuai Lan, Zhiqiang Hu, Lei Wang, Yang Wang, Deheng Ye, Peilin Zhao, Ee-Peng Lim, Hui Xiong, Hao Wang:
LLM-Based Agent Society Investigation: Collaboration and Confrontation in Avalon Gameplay. CoRR abs/2310.14985 (2023) - [i80]Liang Chen, Yatao Bian, Yang Deng, Shuaiyi Li, Bingzhe Wu, Peilin Zhao, Kam-Fai Wong:
X-Mark: Towards Lossless Watermarking Through Lexical Redundancy. CoRR abs/2311.09832 (2023) - 2022
- [j40]Runhao Zeng, Wenbing Huang, Mingkui Tan, Yu Rong, Peilin Zhao, Junzhou Huang, Chuang Gan:
Graph Convolutional Module for Temporal Action Localization in Videos. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 6209-6223 (2022) - [j39]Yong Guo, Yin Zheng, Mingkui Tan, Qi Chen, Zhipeng Li, Jian Chen, Peilin Zhao, Junzhou Huang:
Towards Accurate and Compact Architectures via Neural Architecture Transformer. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 6501-6516 (2022) - [j38]Yifan Zhang, Peilin Zhao, Qingyao Wu, Bin Li, Junzhou Huang, Mingkui Tan:
Cost-Sensitive Portfolio Selection via Deep Reinforcement Learning. IEEE Trans. Knowl. Data Eng. 34(1): 236-248 (2022) - [j37]Peng Han, Shuo Shang, Aixin Sun, Peilin Zhao, Kai Zheng, Xiangliang Zhang:
Point-of-Interest Recommendation With Global and Local Context. IEEE Trans. Knowl. Data Eng. 34(11): 5484-5495 (2022) - [j36]Deheng Ye, Guibin Chen, Peilin Zhao, Fuhao Qiu, Bo Yuan, Wen Zhang, Sheng Chen, Mingfei Sun, Xiaoqian Li, Siqin Li, Jing Liang, Zhenjie Lian, Bei Shi, Liang Wang, Tengfei Shi, Qiang Fu, Wei Yang, Lanxiao Huang:
Supervised Learning Achieves Human-Level Performance in MOBA Games: A Case Study of Honor of Kings. IEEE Trans. Neural Networks Learn. Syst. 33(3): 908-918 (2022) - [c106]Peng Han, Peilin Zhao, Chan Lu, Junzhou Huang, Jiaxiang Wu, Shuo Shang, Bin Yao, Xiangliang Zhang:
GNN-Retro: Retrosynthetic Planning with Graph Neural Networks. AAAI 2022: 4014-4021 - [c105]Jiawei Li, Fan Yang, Fang Wang, Yu Rong, Peilin Zhao, Shizhan Chen, Jianhua Yao, Jijun Tang, Fei Guo:
Integrating Prior Knowledge with Graph Encoder for Gene Regulatory Inference from Single-cell RNA-Seq Data. BIBM 2022: 102-107 - [c104]Yicheng Qian, Weixin Luo, Dongze Lian, Xu Tang, Peilin Zhao, Shenghua Gao:
SVIP: Sequence VerIfication for Procedures in Videos. CVPR 2022: 19858-19870 - [c103]Guoji Fu, Peilin Zhao, Yatao Bian:
p-Laplacian Based Graph Neural Networks. ICML 2022: 6878-6917 - [c102]Songtao Liu, Rex Ying, Hanze Dong, Lanqing Li, Tingyang Xu, Yu Rong, Peilin Zhao, Junzhou Huang, Dinghao Wu:
Local Augmentation for Graph Neural Networks. ICML 2022: 14054-14072 - [c101]Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Yaofo Chen, Shijian Zheng, Peilin Zhao, Mingkui Tan:
Efficient Test-Time Model Adaptation without Forgetting. ICML 2022: 16888-16905 - [c100]Kuangqi Zhou, Kaixin Wang, Jian Tang, Jiashi Feng, Bryan Hooi, Peilin Zhao, Tingyang Xu, Xinchao Wang:
Jointly Modelling Uncertainty and Diversity for Active Molecular Property Prediction. LoG 2022: 29 - [c99]Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu, Changqing Zhang, Jianhua Yao:
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup. NeurIPS 2022 - [c98]Zijing Ou, Tingyang Xu, Qinliang Su, Yingzhen Li, Peilin Zhao, Yatao Bian:
Learning Neural Set Functions Under the Optimal Subset Oracle. NeurIPS 2022 - [c97]Erxue Min, Yu Rong, Tingyang Xu, Yatao Bian, Da Luo, Kangyi Lin, Junzhou Huang, Sophia Ananiadou, Peilin Zhao:
Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer. SIGIR 2022: 353-362 - [c96]Chengqian Gao, Ke Xu, Kuangqi Zhou, Lanqing Li, Xueqian Wang, Bo Yuan, Peilin Zhao:
Value Penalized Q-Learning for Recommender Systems. SIGIR 2022: 2008-2012 - [c95]Erxue Min, Yu Rong, Yatao Bian, Tingyang Xu, Peilin Zhao, Junzhou Huang, Sophia Ananiadou:
Divide-and-Conquer: Post-User Interaction Network for Fake News Detection on Social Media. WWW 2022: 1148-1158 - [i79]Yuanfeng Ji, Lu Zhang, Jiaxiang Wu, Bingzhe Wu, Long-Kai Huang, Tingyang Xu, Yu Rong, Lanqing Li, Jie Ren, Ding Xue, Houtim Lai, Shaoyong Xu, Jing Feng, Wei Liu, Ping Luo, Shuigeng Zhou, Junzhou Huang, Peilin Zhao, Yatao Bian:
DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery - A Focus on Affinity Prediction Problems with Noise Annotations. CoRR abs/2201.09637 (2022) - [i78]Erxue Min, Yu Rong, Tingyang Xu, Yatao Bian, Peilin Zhao, Junzhou Huang, Da Luo, Kangyi Lin, Sophia Ananiadou:
Masked Transformer for Neighhourhood-aware Click-Through Rate Prediction. CoRR abs/2201.13311 (2022) - [i77]Erxue Min, Runfa Chen, Yatao Bian, Tingyang Xu, Kangfei Zhao, Wenbing Huang, Peilin Zhao, Junzhou Huang, Sophia Ananiadou, Yu Rong:
Transformer for Graphs: An Overview from Architecture Perspective. CoRR abs/2202.08455 (2022) - [i76]Zijing Ou, Tingyang Xu, Qinliang Su, Yingzhen Li, Peilin Zhao, Yatao Bian:
Learning Set Functions Under the Optimal Subset Oracle via Equivariant Variational Inference. CoRR abs/2203.01693 (2022) - [i75]Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Guanghui Xu, Haokun Li, Peilin Zhao, Junzhou Huang, Yaowei Wang, Mingkui Tan:
Boost Test-Time Performance with Closed-Loop Inference. CoRR abs/2203.10853 (2022) - [i74]Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Yaofo Chen, Shijian Zheng, Peilin Zhao, Mingkui Tan:
Efficient Test-Time Model Adaptation without Forgetting. CoRR abs/2204.02610 (2022) - [i73]Bingzhe Wu, Zhipeng Liang, Yuxuan Han, Yatao Bian, Peilin Zhao, Junzhou Huang:
DRFLM: Distributionally Robust Federated Learning with Inter-client Noise via Local Mixup. CoRR abs/2204.07742 (2022) - [i72]Qianggang Ding, Deheng Ye, Tingyang Xu, Peilin Zhao:
GPN: A Joint Structural Learning Framework for Graph Neural Networks. CoRR abs/2205.05964 (2022) - [i71]Shibo Feng, Ke Xu, Jiaxiang Wu, Pengcheng Wu, Fan Lin, Peilin Zhao:
Multi-scale Attention Flow for Probabilistic Time Series Forecasting. CoRR abs/2205.07493 (2022) - [i70]Bingzhe Wu, Jintang Li, Junchi Yu, Yatao Bian, Hengtong Zhang, Chaochao Chen, Chengbin Hou, Guoji Fu, Liang Chen, Tingyang Xu, Yu Rong, Xiaolin Zheng, Junzhou Huang, Ran He, Baoyuan Wu, Guangyu Sun, Peng Cui, Zibin Zheng, Zhe Liu, Peilin Zhao:
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. CoRR abs/2205.10014 (2022) - [i69]Liang Zeng, Lanqing Li, Ziqi Gao, Peilin Zhao, Jian Li:
ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification. CoRR abs/2205.11332 (2022) - [i68]Ke Xu, Jianqiao Wangni, Yifan Zhang, Deheng Ye, Jiaxiang Wu, Peilin Zhao:
Quantized Adaptive Subgradient Algorithms and Their Applications. CoRR abs/2208.05631 (2022) - [i67]Lanqing Li, Liang Zeng, Ziqi Gao, Shen Yuan, Yatao Bian, Bingzhe Wu, Hengtong Zhang, Chan Lu, Yang Yu, Wei Liu, Hongteng Xu, Jia Li, Peilin Zhao, Pheng-Ann Heng:
ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug Discovery. CoRR abs/2209.07921 (2022) - [i66]Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu, Changqing Zhang, Jianhua Yao:
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup. CoRR abs/2209.08928 (2022) - [i65]Jiahan Liu, Chaochao Yan, Yang Yu, Chan Lu, Junzhou Huang, Le Ou-Yang, Peilin Zhao:
MARS: A Motif-based Autoregressive Model for Retrosynthesis Prediction. CoRR abs/2209.13178 (2022) - [i64]Songtao Liu, Rex Ying, Zuobai Zhang, Peilin Zhao, Jian Tang, Lu Lin, Dinghao Wu:
Metro: Memory-Enhanced Transformer for Retrosynthetic Planning via Reaction Tree. CoRR abs/2209.15315 (2022) - [i63]Yong Guo, Yaofo Chen, Yin Zheng, Qi Chen, Peilin Zhao, Jian Chen, Junzhou Huang, Mingkui Tan:
Pareto-aware Neural Architecture Generation for Diverse Computational Budgets. CoRR abs/2210.07634 (2022) - [i62]Chengqian Gao, Ke Xu, Liu Liu, Deheng Ye, Peilin Zhao, Zhiqiang Xu:
Robust Offline Reinforcement Learning with Gradient Penalty and Constraint Relaxation. CoRR abs/2210.10469 (2022) - [i61]Zeyu Cao, Zhipeng Liang, Shu Zhang, Hangyu Li, Ouyang Wen, Yu Rong, Peilin Zhao, Bingzhe Wu:
Vertical Federated Linear Contextual Bandits. CoRR abs/2210.11050 (2022) - [i60]Yiqiang Yi, Xu Wan, Kangfei Zhao, Le Ou-Yang, Peilin Zhao:
Predicting Protein-Ligand Binding Affinity with Equivariant Line Graph Network. CoRR abs/2210.16098 (2022) - [i59]Ziqi Gao, Yifan Niu, Jiashun Cheng, Jianheng Tang, Tingyang Xu, Peilin Zhao, Lanqing Li, Fugee Tsung, Jia Li:
Handling Missing Data via Max-Entropy Regularized Graph Autoencoder. CoRR abs/2211.16771 (2022) - 2021
- [j35]Guangxia Li, Jia Liu, Xiao Lu, Peilin Zhao, Yulong Shen, Dusit Niyato:
Decentralized Online Learning With Compressed Communication for Near-Sensor Data Analytics. IEEE Commun. Lett. 25(9): 2958-2962 (2021) - [j34]Xiaoli Li, Peilin Zhao, Min Wu, Zhenghua Chen, Le Zhang:
Deep learning for human activity recognition. Neurocomputing 444: 214-216 (2021) - [j33]Kelong Mao, Xi Xiao, Tingyang Xu, Yu Rong, Junzhou Huang, Peilin Zhao:
Molecular graph enhanced transformer for retrosynthesis prediction. Neurocomputing 457: 193-202 (2021) - [j32]Steven C. H. Hoi, Doyen Sahoo, Jing Lu, Peilin Zhao:
Online learning: A comprehensive survey. Neurocomputing 459: 249-289 (2021) - [j31]Zhibin Hu, Jiachun Wang, Yan Yan, Peilin Zhao, Jian Chen, Jin Huang:
Neural graph personalized ranking for Top-N Recommendation. Knowl. Based Syst. 213: 106426 (2021) - [j30]Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Yong Guo, Peilin Zhao, Junzhou Huang, Mingkui Tan:
Disturbance-immune weight sharing for neural architecture search. Neural Networks 144: 553-564 (2021) - [j29]Yifan Zhang, Peilin Zhao, Shuaicheng Niu, Qingyao Wu, Jiezhang Cao, Junzhou Huang, Mingkui Tan:
Online Adaptive Asymmetric Active Learning With Limited Budgets. IEEE Trans. Knowl. Data Eng. 33(6): 2680-2692 (2021) - [c94]Qin Wang, Boyuan Wang, Zhenlei Xu, Jiaxiang Wu, Peilin Zhao, Zhen Li, Sheng Wang, Junzhou Huang, Shuguang Cui:
PSSM-Distil: Protein Secondary Structure Prediction (PSSP) on Low-Quality PSSM by Knowledge Distillation with Contrastive Learning. AAAI 2021: 617-625 - [c93]Jinyu Yang, Peilin Zhao, Yu Rong, Chaochao Yan, Chunyuan Li, Hehuan Ma, Junzhou Huang:
Hierarchical Graph Capsule Network. AAAI 2021: 10603-10611 - [c92]Congliang Chen, Jiawei Zhang, Li Shen, Peilin Zhao, Zhi-Quan Luo:
Communication Efficient Primal-Dual Algorithm for Nonconvex Nonsmooth Distributed Optimization. AISTATS 2021: 1594-1602 - [c91]Jinyu Yang, Chunyuan Li, Weizhi An, Hehuan Ma, Yuzhi Guo, Yu Rong, Peilin Zhao, Junzhou Huang:
Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation. ICCV 2021: 9174-9183 - [c90]Shuaicheng Niu, Jiaxiang Wu, Guanghui Xu, Yifan Zhang, Yong Guo, Peilin Zhao, Peng Wang, Mingkui Tan:
AdaXpert: Adapting Neural Architecture for Growing Data. ICML 2021: 8184-8194 - [c89]Ying Wei, Peilin Zhao, Junzhou Huang:
Meta-learning Hyperparameter Performance Prediction with Neural Processes. ICML 2021: 11058-11067 - [c88]Minli Li, Peilin Zhao, Yifan Zhang, Shuaicheng Niu, Qingyao Wu, Mingkui Tan:
Structure-aware Mathematical Expression Recognition with Sequence-Level Modeling. ACM Multimedia 2021: 5038-5046 - [c87]Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn:
Meta-learning with an Adaptive Task Scheduler. NeurIPS 2021: 7497-7509 - [c86]Jinyu Yang, Weizhi An, Chaochao Yan, Peilin Zhao, Junzhou Huang:
Context-Aware Domain Adaptation in Semantic Segmentation. WACV 2021: 514-524 - [i58]Yong Guo, Yin Zheng, Mingkui Tan, Qi Chen, Zhipeng Li, Jian Chen, Peilin Zhao, Junzhou Huang:
Towards Accurate and Compact Architectures via Neural Architecture Transformer. CoRR abs/2102.10301 (2021) - [i57]Yong Guo, Yaofo Chen, Yin Zheng, Qi Chen, Peilin Zhao, Jian Chen, Junzhou Huang, Mingkui Tan:
Pareto-Frontier-aware Neural Architecture Generation for Diverse Budgets. CoRR abs/2103.00219 (2021) - [i56]Chaoyang He, Keshav Balasubramanian, Emir Ceyani, Yu Rong, Peilin Zhao, Junzhou Huang, Murali Annavaram, Salman Avestimehr:
FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks. CoRR abs/2104.07145 (2021) - [i55]Dezhong Yao, Peilin Zhao, Chen Yu, Hai Jin, Bin Li:
Sparse online relative similarity learning. CoRR abs/2104.07501 (2021) - [i54]Jinyu Yang, Chunyuan Li, Weizhi An, Hehuan Ma, Yuzhi Guo, Yu Rong, Peilin Zhao, Junzhou Huang:
Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation. CoRR abs/2105.10843 (2021) - [i53]Hongteng Xu, Peilin Zhao, Junzhou Huang, Dixin Luo:
Learning Graphon Autoencoders for Generative Graph Modeling. CoRR abs/2105.14244 (2021) - [i52]Shuaicheng Niu, Jiaxiang Wu, Guanghui Xu, Yifan Zhang, Yong Guo, Peilin Zhao, Peng Wang, Mingkui Tan:
AdaXpert: Adapting Neural Architecture for Growing Data. CoRR abs/2107.00254 (2021) - [i51]Songtao Liu, Hanze Dong, Lanqing Li, Tingyang Xu, Yu Rong, Peilin Zhao, Junzhou Huang, Dinghao Wu:
Local Augmentation for Graph Neural Networks. CoRR abs/2109.03856 (2021) - [i50]Chengqian Gao, Ke Xu, Peilin Zhao:
Value Penalized Q-Learning for Recommender Systems. CoRR abs/2110.07923 (2021) - [i49]Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn:
Meta-learning with an Adaptive Task Scheduler. CoRR abs/2110.14057 (2021) - [i48]Guoji Fu, Peilin Zhao, Yatao Bian:
p-Laplacian Based Graph Neural Networks. CoRR abs/2111.07337 (2021) - [i47]Runhao Zeng, Wenbing Huang, Mingkui Tan, Yu Rong, Peilin Zhao, Junzhou Huang, Chuang Gan:
Graph Convolutional Module for Temporal Action Localization in Videos. CoRR abs/2112.00302 (2021) - [i46]Yicheng Qian, Weixin Luo, Dongze Lian, Xu Tang, Peilin Zhao, Shenghua Gao:
SVIP: Sequence VerIfication for Procedures in Videos. CoRR abs/2112.06447 (2021) - [i45]Chaochao Yan, Peilin Zhao, Chan Lu, Yang Yu, Junzhou Huang:
RetroComposer: Discovering Novel Reactions by Composing Templates for Retrosynthesis Prediction. CoRR abs/2112.11225 (2021) - 2020
- [j28]Xuefei Ning, Yin Zheng, Zhuxi Jiang, Yu Wang, Huazhong Yang, Junzhou Huang, Peilin Zhao:
Nonparametric Topic Modeling with Neural Inference. Neurocomputing 399: 296-306 (2020) - [j27]Guangxia Li, Peilin Zhao, Tao Mei, Peng Yang, Yulong Shen, Kuiyu Chang, Steven C. H. Hoi:
Collaborative online ranking algorithms for multitask learning. Knowl. Inf. Syst. 62(6): 2327-2348 (2020) - [j26]Yifan Zhang, Ying Wei, Qingyao Wu, Peilin Zhao, Shuaicheng Niu, Junzhou Huang, Mingkui Tan:
Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis. IEEE Trans. Image Process. 29: 7834-7844 (2020) - [j25]Peilin Zhao, Dayong Wang, Pengcheng Wu, Steven C. H. Hoi:
A Unified Framework for Sparse Online Learning. ACM Trans. Knowl. Discov. Data 14(5): 59:1-59:20 (2020) - [j24]Xiaoshuang Chen, Yin Zheng, Peilin Zhao, Zhuxi Jiang, Wenye Ma, Junzhou Huang:
A Generalized Locally Linear Factorization Machine with Supervised Variational Encoding. IEEE Trans. Knowl. Data Eng. 32(6): 1036-1049 (2020) - [c85]Tian Bian, Xi Xiao, Tingyang Xu, Peilin Zhao, Wenbing Huang, Yu Rong, Junzhou Huang:
Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks. AAAI 2020: 549-556 - [c84]Deheng Ye, Zhao Liu, Mingfei Sun, Bei Shi, Peilin Zhao, Hao Wu, Hongsheng Yu, Shaojie Yang, Xipeng Wu, Qingwei Guo, Qiaobo Chen, Yinyuting Yin, Hao Zhang, Tengfei Shi, Liang Wang, Qiang Fu, Wei Yang, Lanxiao Huang:
Mastering Complex Control in MOBA Games with Deep Reinforcement Learning. AAAI 2020: 6672-6679 - [c83]Chao Zhang, Jiahao Xie, Zebang Shen, Peilin Zhao, Tengfei Zhou, Hui Qian:
Aggregated Gradient Langevin Dynamics. AAAI 2020: 6746-6753 - [c82]Dongze Lian, Yin Zheng, Yintao Xu, Yanxiong Lu, Leyu Lin, Peilin Zhao, Junzhou Huang, Shenghua Gao:
Towards Fast Adaptation of Neural Architectures with Meta Learning. ICLR 2020 - [c81]Yong Guo, Yaofo Chen, Yin Zheng, Peilin Zhao, Jian Chen, Junzhou Huang, Mingkui Tan:
Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search. ICML 2020: 3822-3831 - [c80]Peng Han, Zhongxiao Li, Yong Liu, Peilin Zhao, Jing Li, Hao Wang, Shuo Shang:
Contextualized Point-of-Interest Recommendation. IJCAI 2020: 2484-2490 - [c79]Ke Xu, Yifan Zhang, Deheng Ye, Peilin Zhao, Mingkui Tan:
Relation-Aware Transformer for Portfolio Policy Learning. IJCAI 2020: 4647-4653 - [c78]Sifan Wu, Xi Xiao, Qianggang Ding, Peilin Zhao, Ying Wei, Junzhou Huang:
Adversarial Sparse Transformer for Time Series Forecasting. NeurIPS 2020 - [c77]Chaochao Yan, Qianggang Ding, Peilin Zhao, Shuangjia Zheng, Jinyu Yang, Yang Yu, Junzhou Huang:
RetroXpert: Decompose Retrosynthesis Prediction Like A Chemist. NeurIPS 2020 - [i44]Tian Bian, Xi Xiao, Tingyang Xu, Peilin Zhao, Wenbing Huang, Yu Rong, Junzhou Huang:
Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks. CoRR abs/2001.06362 (2020) - [i43]Jiezhang Cao, Langyuan Mo, Qing Du, Yong Guo, Peilin Zhao, Junzhou Huang, Mingkui Tan:
Joint Wasserstein Distribution Matching. CoRR abs/2003.00389 (2020) - [i42]Yifan Zhang, Peilin Zhao, Qingyao Wu, Bin Li, Junzhou Huang, Mingkui Tan:
Cost-Sensitive Portfolio Selection via Deep Reinforcement Learning. CoRR abs/2003.03051 (2020) - [i41]Jinyu Yang, Weizhi An, Chaochao Yan, Peilin Zhao, Junzhou Huang:
Context-Aware Domain Adaptation in Semantic Segmentation. CoRR abs/2003.04010 (2020) - [i40]Chaochao Chen, Ziqi Liu, Peilin Zhao, Jun Zhou, Xiaolong Li:
Privacy Preserving Point-of-interest Recommendation Using Decentralized Matrix Factorization. CoRR abs/2003.05610 (2020) - [i39]Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Yong Guo, Peilin Zhao, Junzhou Huang, Mingkui Tan:
Disturbance-immune Weight Sharing for Neural Architecture Search. CoRR abs/2003.13089 (2020) - [i38]Yifan Zhang, Shuaicheng Niu, Zhen Qiu, Ying Wei, Peilin Zhao, Jianhua Yao, Junzhou Huang, Qingyao Wu, Mingkui Tan:
COVID-DA: Deep Domain Adaptation from Typical Pneumonia to COVID-19. CoRR abs/2005.01577 (2020) - [i37]Tian Bian, Xi Xiao, Tingyang Xu, Yu Rong, Wenbing Huang, Peilin Zhao, Junzhou Huang:
Inverse Graph Identification: Can We Identify Node Labels Given Graph Labels? CoRR abs/2007.05970 (2020) - [i36]Yong Guo, Yaofo Chen, Yin Zheng, Peilin Zhao, Jian Chen, Junzhou Huang, Mingkui Tan:
Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search. CoRR abs/2007.07197 (2020) - [i35]Yifan Zhang, Ying Wei, Qingyao Wu, Peilin Zhao, Shuaicheng Niu, Junzhou Huang, Mingkui Tan:
Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis. CoRR abs/2007.07222 (2020) - [i34]Chaoyang He, Songze Li, Jinhyun So, Mi Zhang, Hongyi Wang, Xiaoyang Wang, Praneeth Vepakomma, Abhishek Singh, Hang Qiu, Li Shen, Peilin Zhao, Yan Kang, Yang Liu, Ramesh Raskar, Qiang Yang, Murali Annavaram, Salman Avestimehr:
FedML: A Research Library and Benchmark for Federated Machine Learning. CoRR abs/2007.13518 (2020) - [i33]Chaochao Yan, Qianggang Ding, Peilin Zhao, Shuangjia Zheng, Jinyu Yang, Yang Yu, Junzhou Huang:
RetroXpert: Decompose Retrosynthesis Prediction like a Chemist. CoRR abs/2011.02893 (2020) - [i32]Deheng Ye, Guibin Chen, Peilin Zhao, Fuhao Qiu, Bo Yuan, Wen Zhang, Sheng Chen, Mingfei Sun, Xiaoqian Li, Siqin Li, Jing Liang, Zhenjie Lian, Bei Shi, Liang Wang, Tengfei Shi, Qiang Fu, Wei Yang, Lanxiao Huang:
Supervised Learning Achieves Human-Level Performance in MOBA Games: A Case Study of Honor of Kings. CoRR abs/2011.12582 (2020) - [i31]Jinyu Yang, Peilin Zhao, Yu Rong, Chaochao Yan, Chunyuan Li, Hehuan Ma, Junzhou Huang:
Hierarchical Graph Capsule Network. CoRR abs/2012.08734 (2020)
2010 – 2019
- 2019
- [j23]Guangxia Li, Yulong Shen, Peilin Zhao, Xiao Lu, Jia Liu, Yangyang Liu, Steven C. H. Hoi:
Detecting cyberattacks in industrial control systems using online learning algorithms. Neurocomputing 364: 338-348 (2019) - [j22]Peilin Zhao, Yifan Zhang, Min Wu, Steven C. H. Hoi, Mingkui Tan, Junzhou Huang:
Adaptive Cost-Sensitive Online Classification. IEEE Trans. Knowl. Data Eng. 31(2): 214-228 (2019) - [c76]Peng Yang, Peilin Zhao, Jiayu Zhou, Xin Gao:
Confidence Weighted Multitask Learning. AAAI 2019: 5636-5643 - [c75]Zebang Shen, Cong Fang, Peilin Zhao, Junzhou Huang, Hui Qian:
Complexities in Projection-Free Stochastic Non-convex Minimization. AISTATS 2019: 2868-2876 - [c74]Guangxia Li, Peilin Zhao, Xiao Lu, Jia Liu, Yulong Shen:
Data Analytics for Fog Computing by Distributed Online Learning with Asynchronous Update. ICC 2019: 1-6 - [c73]Runhao Zeng, Wenbing Huang, Chuang Gan, Mingkui Tan, Yu Rong, Peilin Zhao, Junzhou Huang:
Graph Convolutional Networks for Temporal Action Localization. ICCV 2019: 7093-7102 - [c72]Peng Han, Shuo Shang, Aixin Sun, Peilin Zhao, Kai Zheng, Panos Kalnis:
AUC-MF: Point of Interest Recommendation with AUC Maximization. ICDE 2019: 1558-1561 - [c71]Chi Zhang, Qianxiao Li, Peilin Zhao:
Decentralized Optimization with Edge Sampling. IJCAI 2019: 658-664 - [c70]Wen Liu, Weixin Luo, Zhengxin Li, Peilin Zhao, Shenghua Gao:
Margin Learning Embedded Prediction for Video Anomaly Detection with A Few Anomalies. IJCAI 2019: 3023-3030 - [c69]Peng Han, Peng Yang, Peilin Zhao, Shuo Shang, Yong Liu, Jiayu Zhou, Xin Gao, Panos Kalnis:
GCN-MF: Disease-Gene Association Identification By Graph Convolutional Networks and Matrix Factorization. KDD 2019: 705-713 - [c68]Yifan Zhang, Hanbo Chen, Ying Wei, Peilin Zhao, Jiezhang Cao, Xinjuan Fan, Xiaoying Lou, Hailing Liu, Jinlong Hou, Xiao Han, Jianhua Yao, Qingyao Wu, Mingkui Tan, Junzhou Huang:
From Whole Slide Imaging to Microscopy: Deep Microscopy Adaptation Network for Histopathology Cancer Image Classification. MICCAI (1) 2019: 360-368 - [c67]Yong Guo, Yin Zheng, Mingkui Tan, Qi Chen, Jian Chen, Peilin Zhao, Junzhou Huang:
NAT: Neural Architecture Transformer for Accurate and Compact Architectures. NeurIPS 2019: 735-747 - [c66]Ho Chung Leon Law, Peilin Zhao, Leung Sing Chan, Junzhou Huang, Dino Sejdinovic:
Hyperparameter Learning via Distributional Transfer. NeurIPS 2019: 6801-6812 - [c65]Chenghao Liu, Teng Zhang, Jundong Li, Jianwen Yin, Peilin Zhao, Jianling Sun, Steven C. H. Hoi:
Robust Factorization Machine: A Doubly Capped Norms Minimization. SDM 2019: 738-746 - [i30]Yawei Zhao, Chen Yu, Peilin Zhao, Ji Liu:
Decentralized Online Learning: Take Benefits from Others' Data without Sharing Your Own to Track Global Trend. CoRR abs/1901.10593 (2019) - [i29]Ying Wei, Peilin Zhao, Huaxiu Yao, Junzhou Huang:
Transferable Neural Processes for Hyperparameter Optimization. CoRR abs/1909.03209 (2019) - [i28]Runhao Zeng, Wenbing Huang, Mingkui Tan, Yu Rong, Peilin Zhao, Junzhou Huang, Chuang Gan:
Graph Convolutional Networks for Temporal Action Localization. CoRR abs/1909.03252 (2019) - [i27]Chao Zhang, Jiahao Xie, Zebang Shen, Peilin Zhao, Tengfei Zhou, Hui Qian:
Aggregated Gradient Langevin Dynamics. CoRR abs/1910.09223 (2019) - [i26]Yong Guo, Yin Zheng, Mingkui Tan, Qi Chen, Jian Chen, Peilin Zhao, Junzhou Huang:
NAT: Neural Architecture Transformer for Accurate and Compact Architectures. CoRR abs/1910.14488 (2019) - [i25]Yifan Zhang, Ying Wei, Peilin Zhao, Shuaicheng Niu, Qingyao Wu, Mingkui Tan, Junzhou Huang:
Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis. CoRR abs/1911.07293 (2019) - [i24]Yifan Zhang, Peilin Zhao, Shuaicheng Niu, Qingyao Wu, Jiezhang Cao, Junzhou Huang, Mingkui Tan:
Online Adaptive Asymmetric Active Learning with Limited Budgets. CoRR abs/1911.07498 (2019) - [i23]Guangxia Li, Yulong Shen, Peilin Zhao, Xiao Lu, Jia Liu, Yangyang Liu, Steven C. H. Hoi:
Detecting Cyberattacks in Industrial Control Systems Using Online Learning Algorithms. CoRR abs/1912.03589 (2019) - [i22]Deheng Ye, Zhao Liu, Mingfei Sun, Bei Shi, Peilin Zhao, Hao Wu, Hongsheng Yu, Shaojie Yang, Xipeng Wu, Qingwei Guo, Qiaobo Chen, Yinyuting Yin, Hao Zhang, Tengfei Shi, Liang Wang, Qiang Fu, Wei Yang, Lanxiao Huang:
Mastering Complex Control in MOBA Games with Deep Reinforcement Learning. CoRR abs/1912.09729 (2019) - 2018
- [j21]Chi Zhang, Peilin Zhao, Shuji Hao, Yeng Chai Soh, Bu-Sung Lee, Chunyan Miao, Steven C. H. Hoi:
Distributed multi-task classification: a decentralized online learning approach. Mach. Learn. 107(4): 727-747 (2018) - [j20]Jing Lu, Doyen Sahoo, Peilin Zhao, Steven C. H. Hoi:
Sparse Passive-Aggressive Learning for Bounded Online Kernel Methods. ACM Trans. Intell. Syst. Technol. 9(4): 45:1-45:27 (2018) - [j19]Shuji Hao, Peiying Hu, Peilin Zhao, Steven C. H. Hoi, Chunyan Miao:
Online Active Learning with Expert Advice. ACM Trans. Knowl. Discov. Data 12(5): 58:1-58:22 (2018) - [j18]Shuji Hao, Jing Lu, Peilin Zhao, Chi Zhang, Steven C. H. Hoi, Chunyan Miao:
Second-Order Online Active Learning and Its Applications. IEEE Trans. Knowl. Data Eng. 30(7): 1338-1351 (2018) - [c64]Chaochao Chen, Ziqi Liu, Peilin Zhao, Jun Zhou, Xiaolong Li:
Privacy Preserving Point-of-Interest Recommendation Using Decentralized Matrix Factorization. AAAI 2018: 257-264 - [c63]Chenghao Liu, Teng Zhang, Peilin Zhao, Jianling Sun, Steven C. H. Hoi:
Unified Locally Linear Classifiers With Diversity-Promoting Anchor Points. AAAI 2018: 2339-2346 - [c62]Zebang Shen, Aryan Mokhtari, Tengfei Zhou, Peilin Zhao, Hui Qian:
Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication. ICML 2018: 4631-4640 - [c61]Peng Yang, Peilin Zhao, Xin Gao:
Bandit Online Learning on Graphs via Adaptive Optimization. IJCAI 2018: 2991-2997 - [c60]Dezhong Yao, Peilin Zhao, Tuan-Anh Nguyen Pham, Gao Cong:
High-dimensional Similarity Learning via Dual-sparse Random Projection. IJCAI 2018: 3005-3011 - [c59]Chaochao Chen, Ziqi Liu, Peilin Zhao, Longfei Li, Jun Zhou, Xiaolong Li:
Distributed Collaborative Hashing and Its Applications in Ant Financial. KDD 2018: 100-109 - [c58]Yifan Zhang, Peilin Zhao, Jiezhang Cao, Wenye Ma, Junzhou Huang, Qingyao Wu, Mingkui Tan:
Online Adaptive Asymmetric Active Learning for Budgeted Imbalanced Data. KDD 2018: 2768-2777 - [c57]Xinxing Yang, Jun Zhou, Peilin Zhao, Cen Chen, Chaochao Chen, Xiaolong Li:
A Local Online Learning Approach for Non-linear Data. PAKDD (2) 2018: 431-443 - [c56]Peng Yang, Peilin Zhao, Yong Liu, Xin Gao:
Robust Cost-Sensitive Learning for Recommendation with Implicit Feedback. SDM 2018: 621-629 - [c55]Peng Yang, Peilin Zhao, Vincent W. Zheng, Lizhong Ding, Xin Gao:
Robust Asymmetric Recommendation via Min-Max Optimization. SIGIR 2018: 1077-1080 - [c54]Xiao Lin, Wenpeng Zhang, Min Zhang, Wenwu Zhu, Jian Pei, Peilin Zhao, Junzhou Huang:
Online Compact Convexified Factorization Machine. WWW 2018: 1633-1642 - [r1]Guangxia Li, Zhen Hai, Peilin Zhao, Kuiyu Chang, Steven C. H. Hoi:
Twitter Microblog Sentiment Analysis. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - [i21]Wenpeng Zhang, Xiao Lin, Peilin Zhao:
Online Compact Convexified Factorization Machine. CoRR abs/1802.01379 (2018) - [i20]Steven C. H. Hoi, Doyen Sahoo, Jing Lu, Peilin Zhao:
Online Learning: A Comprehensive Survey. CoRR abs/1802.02871 (2018) - [i19]Peilin Zhao, Yifan Zhang, Min Wu, Steven C. H. Hoi, Mingkui Tan, Junzhou Huang:
Adaptive Cost-sensitive Online Classification. CoRR abs/1804.02246 (2018) - [i18]Chaochao Chen, Ziqi Liu, Peilin Zhao, Longfei Li, Jun Zhou, Xiaolong Li:
Distributed Collaborative Hashing and Its Applications in Ant Financial. CoRR abs/1804.04918 (2018) - [i17]Longfei Li, Peilin Zhao, Jun Zhou, Xiaolong Li:
A Boosting Framework of Factorization Machine. CoRR abs/1804.06027 (2018) - [i16]Zebang Shen, Aryan Mokhtari, Tengfei Zhou, Peilin Zhao, Hui Qian:
Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication. CoRR abs/1805.09969 (2018) - [i15]Yong Guo, Qi Chen, Jian Chen, Junzhou Huang, Yanwu Xu, Jiezhang Cao, Peilin Zhao, Mingkui Tan:
Dual Reconstruction Nets for Image Super-Resolution with Gradient Sensitive Loss. CoRR abs/1809.07099 (2018) - [i14]Ho Chung Leon Law, Peilin Zhao, Junzhou Huang, Dino Sejdinovic:
Hyperparameter Learning via Distributional Transfer. CoRR abs/1810.06305 (2018) - 2017
- [j17]Chenghao Liu, Tao Jin, Steven C. H. Hoi, Peilin Zhao, Jianling Sun:
Collaborative topic regression for online recommender systems: an online and Bayesian approach. Mach. Learn. 106(5): 651-670 (2017) - [j16]Ali Ezzat, Peilin Zhao, Min Wu, Xiaoli Li, Chee Keong Kwoh:
Drug-Target Interaction Prediction with Graph Regularized Matrix Factorization. IEEE ACM Trans. Comput. Biol. Bioinform. 14(3): 646-656 (2017) - [j15]Peng Yang, Peilin Zhao, Xin Gao:
Robust Online Multi-Task Learning with Correlative and Personalized Structures. IEEE Trans. Knowl. Data Eng. 29(11): 2510-2521 (2017) - [c53]Yi Ding, Chenghao Liu, Peilin Zhao, Steven C. H. Hoi:
Large Scale Kernel Methods for Online AUC Maximization. ICDM 2017: 91-100 - [c52]Minghui Qiu, Peilin Zhao, Ke Zhang, Jun Huang, Xing Shi, Xiaoguang Wang, Wei Chu:
A Short-Term Rainfall Prediction Model Using Multi-task Convolutional Neural Networks. ICDM 2017: 395-404 - [c51]Wenpeng Zhang, Peilin Zhao, Wenwu Zhu, Steven C. H. Hoi, Tong Zhang:
Projection-free Distributed Online Learning in Networks. ICML 2017: 4054-4062 - [c50]Shuji Hao, Peilin Zhao, Yong Liu, Steven C. H. Hoi, Chunyan Miao:
Online Multitask Relative Similarity Learning. IJCAI 2017: 1823-1829 - [c49]Chenghao Liu, Teng Zhang, Peilin Zhao, Jun Zhou, Jianling Sun:
Locally Linear Factorization Machines. IJCAI 2017: 2294-2300 - [c48]Yong Liu, Peilin Zhao, Xin Liu, Min Wu, Lixin Duan, Xiaoli Li:
Learning User Dependencies for Recommendation. IJCAI 2017: 2379-2385 - [c47]Jun Zhou, Xiaolong Li, Peilin Zhao, Chaochao Chen, Longfei Li, Xinxing Yang, Qing Cui, Jin Yu, Xu Chen, Yi Ding, Yuan (Alan) Qi:
KunPeng: Parameter Server based Distributed Learning Systems and Its Applications in Alibaba and Ant Financial. KDD 2017: 1693-1702 - [c46]Cen Chen, Peilin Zhao, Longfei Li, Jun Zhou, Xiaolong Li, Minghui Qiu:
Locally Connected Deep Learning Framework for Industrial-scale Recommender Systems. WWW (Companion Volume) 2017: 769-770 - [c45]Jun Zhou, Qing Cui, Xiaolong Li, Peilin Zhao, Shenquan Qu, Jun Huang:
PSMART: Parameter Server based Multiple Additive Regression Trees System. WWW (Companion Volume) 2017: 879-880 - [i13]Peng Yang, Peilin Zhao, Xin Gao:
Robust Online Multi-Task Learning with Correlative and Personalized Structures. CoRR abs/1706.01824 (2017) - [i12]Peng Yang, Peilin Zhao, Xin Gao, Yong Liu:
Robust Cost-Sensitive Learning for Recommendation with Implicit Feedback. CoRR abs/1707.00536 (2017) - 2016
- [j14]Jing Lu, Steven C. H. Hoi, Jialei Wang, Peilin Zhao, Zhiyong Liu:
Large Scale Online Kernel Learning. J. Mach. Learn. Res. 17: 47:1-47:43 (2016) - [j13]Jing Lu, Peilin Zhao, Steven C. H. Hoi:
Online Passive-Aggressive Active learning. Mach. Learn. 103(2): 141-183 (2016) - [j12]Yong Liu, Min Wu, Chunyan Miao, Peilin Zhao, Xiaoli Li:
Neighborhood Regularized Logistic Matrix Factorization for Drug-Target Interaction Prediction. PLoS Comput. Biol. 12(2) (2016) - [j11]Jialei Wang, Peilin Zhao, Steven C. H. Hoi:
Soft Confidence-Weighted Learning. ACM Trans. Intell. Syst. Technol. 8(1): 15:1-15:32 (2016) - [j10]Pengcheng Wu, Steven C. H. Hoi, Peilin Zhao, Chunyan Miao, Zhiyong Liu:
Online Multi-Modal Distance Metric Learning with Application to Image Retrieval. IEEE Trans. Knowl. Data Eng. 28(2): 454-467 (2016) - [c44]Chenghao Liu, Steven C. H. Hoi, Peilin Zhao, Jianling Sun:
Online ARIMA Algorithms for Time Series Prediction. AAAI 2016: 1867-1873 - [c43]Doyen Sahoo, Steven C. H. Hoi, Peilin Zhao:
Cost Sensitive Online Multiple Kernel Classification. ACML 2016: 65-80 - [c42]Chenghao Liu, Steven C. H. Hoi, Peilin Zhao, Jianling Sun, Ee-Peng Lim:
Online Adaptive Passive-Aggressive Methods for Non-Negative Matrix Factorization and Its Applications. CIKM 2016: 1161-1170 - [c41]Giduthuri Sateesh Babu, Peilin Zhao, Xiaoli Li:
Deep Convolutional Neural Network Based Regression Approach for Estimation of Remaining Useful Life. DASFAA (1) 2016: 214-228 - [c40]Zhen Hai, Peilin Zhao, Peng Cheng, Peng Yang, Xiaoli Li, Guangxia Li:
Deceptive Review Spam Detection via Exploiting Task Relatedness and Unlabeled Data. EMNLP 2016: 1817-1826 - [c39]Shuji Hao, Peilin Zhao, Jing Lu, Steven C. H. Hoi, Chunyan Miao, Chi Zhang:
SOAL: Second-Order Online Active Learning. ICDM 2016: 931-936 - [c38]Chi Zhang, Peilin Zhao, Shuji Hao, Yeng Chai Soh, Bu-Sung Lee:
ROM: A Robust Online Multi-task Learning Approach. ICDM 2016: 1341-1346 - [c37]Zhiqiang Xu, Peilin Zhao, Jianneng Cao, Xiaoli Li:
Matrix Eigen-decomposition via Doubly Stochastic Riemannian Optimization. ICML 2016: 1660-1669 - [c36]Guimei Liu, Tam T. Nguyen, Gang Zhao, Wei Zha, Jianbo Yang, Jianneng Cao, Min Wu, Peilin Zhao, Wei Chen:
Repeat Buyer Prediction for E-Commerce. KDD 2016: 155-164 - [c35]Doyen Sahoo, Abhishek Sharma, Steven C. H. Hoi, Peilin Zhao:
Temporal Kernel Descriptors for Learning with Time-sensitive Patterns. SDM 2016: 540-548 - [c34]Peng Yang, Guangxia Li, Peilin Zhao, Xiaoli Li, Sujatha Das Gollapalli:
Learning Correlative and Personalized Structure for Online Multi-Task Classification. SDM 2016: 666-674 - [c33]Jing Lu, Peilin Zhao, Steven C. H. Hoi:
Online Sparse Passive Aggressive Learning with Kernels. SDM 2016: 675-683 - [c32]Peng Yang, Peilin Zhao, Zhen Hai, Wei Liu, Steven C. H. Hoi, Xiaoli Li:
Efficient Multi-Class Selective Sampling on Graphs. UAI 2016 - [i11]Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong:
Adaptive Subgradient Methods for Online AUC Maximization. CoRR abs/1602.00351 (2016) - [i10]Yong Liu, Peilin Zhao, Xin Liu, Min Wu, Xiaoli Li:
Learning Optimal Social Dependency for Recommendation. CoRR abs/1603.04522 (2016) - [i9]Chenghao Liu, Tao Jin, Steven C. H. Hoi, Peilin Zhao, Jianling Sun:
Online Bayesian Collaborative Topic Regression. CoRR abs/1605.08872 (2016) - 2015
- [c31]Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong:
An Adaptive Gradient Method for Online AUC Maximization. AAAI 2015: 2568-2574 - [c30]Peng Yang, Peilin Zhao:
A Min-Max Optimization Framework For Online Graph Classification. CIKM 2015: 643-652 - [c29]Shuji Hao, Peilin Zhao, Steven C. H. Hoi, Chunyan Miao:
Learning Relative Similarity from Data Streams: Active Online Learning Approaches. CIKM 2015: 1181-1190 - [c28]Peng Yang, Peilin Zhao, Vincent W. Zheng, Xiaoli Li:
An Aggressive Graph-Based Selective Sampling Algorithm for Classification. ICDM 2015: 509-518 - [c27]Dezhong Yao, Peilin Zhao, Chen Yu, Hai Jin, Bin Li:
Sparse Online Relative Similarity Learning. ICDM 2015: 529-538 - [c26]Peilin Zhao, Furen Zhuang, Min Wu, Xiaoli Li, Steven C. H. Hoi:
Cost-Sensitive Online Classification with Adaptive Regularization and Its Applications. ICDM 2015: 649-658 - [c25]Peilin Zhao, Tong Zhang:
Stochastic Optimization with Importance Sampling for Regularized Loss Minimization. ICML 2015: 1-9 - [c24]Peilin Zhao, Jinwei Yang, Tong Zhang, Ping Li:
Adaptive Stochastic Alternating Direction Method of Multipliers. ICML 2015: 69-77 - [c23]Yong Liu, Peilin Zhao, Aixin Sun, Chunyan Miao:
A Boosting Algorithm for Item Recommendation with Implicit Feedback. IJCAI 2015: 1792-1798 - [c22]Ji Wan, Pengcheng Wu, Steven C. H. Hoi, Peilin Zhao, Xingyu Gao, Dayong Wang, Yongdong Zhang, Jintao Li:
Online Learning to Rank for Content-Based Image Retrieval. IJCAI 2015: 2284-2290 - [c21]Shuji Hao, Steven C. H. Hoi, Chunyan Miao, Peilin Zhao:
Active Crowdsourcing for Annotation. WI-IAT (2) 2015: 1-8 - [i8]Dayong Wang, Pengcheng Wu, Peilin Zhao, Steven C. H. Hoi:
A Framework of Sparse Online Learning and Its Applications. CoRR abs/1507.07146 (2015) - [i7]Jing Lu, Steven C. H. Hoi, Doyen Sahoo, Peilin Zhao:
Budget Online Multiple Kernel Learning. CoRR abs/1511.04813 (2015) - 2014
- [j9]Peilin Zhao, Steven C. H. Hoi, Jialei Wang, Bin Li:
Online Transfer Learning. Artif. Intell. 216: 76-102 (2014) - [j8]Steven C. H. Hoi, Jialei Wang, Peilin Zhao:
LIBOL: a library for online learning algorithms. J. Mach. Learn. Res. 15(1): 495-499 (2014) - [j7]Hao Xia, Steven C. H. Hoi, Rong Jin, Peilin Zhao:
Online Multiple Kernel Similarity Learning for Visual Search. IEEE Trans. Pattern Anal. Mach. Intell. 36(3): 536-549 (2014) - [j6]Jialei Wang, Peilin Zhao, Steven C. H. Hoi, Rong Jin:
Online Feature Selection and Its Applications. IEEE Trans. Knowl. Data Eng. 26(3): 698-710 (2014) - [j5]Jialei Wang, Peilin Zhao, Steven C. H. Hoi:
Cost-Sensitive Online Classification. IEEE Trans. Knowl. Data Eng. 26(10): 2425-2438 (2014) - [c20]Pengcheng Wu, Yi Ding, Peilin Zhao, Chunyan Miao, Steven C. H. Hoi:
Learning Relative Similarity by Stochastic Dual Coordinate Ascent. AAAI 2014: 2142-2148 - [c19]Jing Lu, Peilin Zhao, Steven C. H. Hoi:
Online Passive Aggressive Active Learning and Its Applications. ACML 2014 - [c18]Dayong Wang, Pengcheng Wu, Peilin Zhao, Yue Wu, Chunyan Miao, Steven C. H. Hoi:
High-Dimensional Data Stream Classification via Sparse Online Learning. ICDM 2014: 1007-1012 - [i6]Peilin Zhao, Tong Zhang:
Stochastic Optimization with Importance Sampling. CoRR abs/1401.2753 (2014) - [i5]Peilin Zhao, Tong Zhang:
Accelerating Minibatch Stochastic Gradient Descent using Stratified Sampling. CoRR abs/1405.3080 (2014) - 2013
- [b1]Peilin Zhao:
Kernel based online learning. Nanyang Technological University, Singapore, 2013 - [j4]Steven C. H. Hoi, Rong Jin, Peilin Zhao, Tianbao Yang:
Online Multiple Kernel Classification. Mach. Learn. 90(2): 289-316 (2013) - [j3]Bin Li, Steven C. H. Hoi, Peilin Zhao, Vivekanand Gopalkrishnan:
Confidence Weighted Mean Reversion Strategy for Online Portfolio Selection. ACM Trans. Knowl. Discov. Data 7(1): 4:1-4:38 (2013) - [c17]Steven C. H. Hoi, Jialei Wang, Peilin Zhao, Jinfeng Zhuang, Zhiyong Liu:
Large Scale Online Kernel Classification. IJCAI 2013: 1750-1756 - [c16]Peilin Zhao, Steven C. H. Hoi:
Cost-sensitive online active learning with application to malicious URL detection. KDD 2013: 919-927 - [c15]Pengcheng Wu, Steven C. H. Hoi, Hao Xia, Peilin Zhao, Dayong Wang, Chunyan Miao:
Online multimodal deep similarity learning with application to image retrieval. ACM Multimedia 2013: 153-162 - [c14]Jialei Wang, Steven C. H. Hoi, Peilin Zhao, Zhiyong Liu:
Online multi-task collaborative filtering for on-the-fly recommender systems. RecSys 2013: 237-244 - [c13]Steven C. H. Hoi, Peilin Zhao:
Cost-Sensitive Double Updating Online Learning and Its Application to Online Anomaly Detection. SDM 2013: 207-215 - [c12]Peilin Zhao, Steven C. H. Hoi, Jinfeng Zhuang:
Active Learning with Expert Advice. UAI 2013 - [i4]Peilin Zhao, Steven C. H. Hoi, Jinfeng Zhuang:
Active Learning with Expert Advice. CoRR abs/1309.6875 (2013) - [i3]Peilin Zhao, Jinwei Yang, Tong Zhang, Ping Li:
Accelerating Stochastic Alternating Direction Method of Multipliers with Adaptive Subgradient. CoRR abs/1312.4564 (2013) - 2012
- [j2]Bin Li, Peilin Zhao, Steven C. H. Hoi, Vivekanand Gopalkrishnan:
PAMR: Passive aggressive mean reversion strategy for portfolio selection. Mach. Learn. 87(2): 221-258 (2012) - [c11]Jialei Wang, Peilin Zhao, Steven C. H. Hoi:
Cost-Sensitive Online Classification. ICDM 2012: 1140-1145 - [c10]Steven C. H. Hoi, Jialei Wang, Peilin Zhao:
Exact Soft Confidence-Weighted Learning. ICML 2012 - [c9]Steven C. H. Hoi, Jialei Wang, Peilin Zhao, Rong Jin, Pengcheng Wu:
Fast Bounded Online Gradient Descent Algorithms for Scalable Kernel-Based Online Learning. ICML 2012 - [c8]Steven C. H. Hoi, Jialei Wang, Peilin Zhao, Rong Jin:
Online feature selection for mining big data. BigMine 2012: 93-100 - [c7]Peilin Zhao, Steven C. H. Hoi:
BDUOL: Double Updating Online Learning on a Fixed Budget. ECML/PKDD (1) 2012: 810-826 - [i2]Jialei Wang, Peilin Zhao, Steven C. H. Hoi:
Exact Soft Confidence-Weighted Learning. CoRR abs/1206.4612 (2012) - [i1]Peilin Zhao, Jialei Wang, Pengcheng Wu, Rong Jin, Steven C. H. Hoi:
Fast Bounded Online Gradient Descent Algorithms for Scalable Kernel-Based Online Learning. CoRR abs/1206.4633 (2012) - 2011
- [j1]Peilin Zhao, Steven C. H. Hoi, Rong Jin:
Double Updating Online Learning. J. Mach. Learn. Res. 12: 1587-1615 (2011) - [c6]Peilin Zhao, Steven C. H. Hoi, Rong Jin, Tianbao Yang:
Online AUC Maximization. ICML 2011: 233-240 - [c5]Pengcheng Wu, Steven C. H. Hoi, Peilin Zhao, Ying He:
Mining social images with distance metric learning for automated image tagging. WSDM 2011: 197-206 - [c4]Bin Li, Steven C. H. Hoi, Peilin Zhao, Vivekanand Gopalkrishnan:
Confidence Weighted Mean Reversion Strategy for On-Line Portfolio Selection. AISTATS 2011: 434-442 - 2010
- [c3]Shenghua Gao, Ivor Wai-Hung Tsang, Liang-Tien Chia, Peilin Zhao:
Local features are not lonely - Laplacian sparse coding for image classification. CVPR 2010: 3555-3561 - [c2]Peilin Zhao, Steven C. H. Hoi:
OTL: A Framework of Online Transfer Learning. ICML 2010: 1231-1238
2000 – 2009
- 2009
- [c1]Peilin Zhao, Steven C. H. Hoi, Rong Jin:
DUOL: A Double Updating Approach for Online Learning. NIPS 2009: 2259-2267
Coauthor Index
[j32] [j27] [j25] [j23] [j22] [c65] [i23] [j21] [j20] [j19] [j18] [c63] [r1] [i20] [i19] [j17] [c53] [c51] [c50] [j14] [j13] [j11] [j10] [c44] [c43] [c42] [c39] [c35] [c33] [c32] [i11] [i9] [c31] [c29] [c26] [c22] [c21] [i8] [i7] [j9] [j8] [j7] [j6] [j5] [c20] [c19] [c18] [j4] [j3] [c17] [c16] [c15] [c14] [c13] [c12] [i4] [j2] [c11] [c10] [c9] [c8] [c7] [i2] [i1] [j1] [c6] [c5] [c4] [c2] [c1]
[c128] [c124] [c121] [c112] [c107] [j40] [j39] [j38] [c106] [c102] [c97] [c95] [i79] [i78] [i77] [i75] [i73] [i70] [i65] [i63] [j33] [j30] [j29] [c94] [c93] [c91] [c89] [c86] [i58] [i57] [i56] [i54] [i53] [i51] [i47] [i45] [j28] [j26] [j24] [c85] [c82] [c81] [c78] [c77] [i44] [i43] [i42] [i41] [i39] [i38] [i37] [i36] [i35] [i33] [i31] [j22] [c75] [c73] [c68] [c67] [c66] [i29] [i28] [i26] [i25] [i24] [c58] [c54] [i19] [i15] [i14]
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