Zhao, Peilin

118 publications

TMLR 2025 Are Large Language Models Really Robust to Word-Level Perturbations? 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

ICLR 2025 COME: Test-Time Adaption by Conservatively Minimizing Entropy Qingyang Zhang, Yatao Bian, Xinke Kong, Peilin Zhao, Changqing Zhang

NeurIPS 2025 Continual Optimization with Symmetry Teleportation for Multi-Task Learning Zhipeng Zhou, Ziqiao Meng, Pengcheng Wu, Peilin Zhao, Chunyan Miao

ICML 2025 Efficient Parallel Training Methods for Spiking Neural Networks with Constant Time Complexity Wanjin Feng, Xingyu Gao, Wenqian Du, Hailong Shi, Peilin Zhao, Pengcheng Wu, Chunyan Miao

NeurIPS 2025 Exploring Tradeoffs Through Mode Connectivity for Multi-Task Learning Zhipeng Zhou, Ziqiao Meng, Pengcheng Wu, Peilin Zhao, Chunyan Miao

ICLRW 2025 Fast and Accurate Antibody Sequence Design via Structure Retrieval Xingyi Zhang, Kun Xie, Ningqiao Huang, Wei Liu, Peilin Zhao, Sibo Wang, Kangfei Zhao, Biaobin Jiang

NeurIPS 2025 Geometric Algebra-Enhanced Bayesian Flow Network for RNA Inverse Design Rubo Wang, Xingyu Gao, Peilin Zhao

AAAI 2025 HDT: Hierarchical Discrete Transformer for Multivariate Time Series Forecasting Shibo Feng, Peilin Zhao, Liu Liu, Pengcheng Wu, Zhiqi Shen

ICLR 2025 IgGM: A Generative Model for Functional Antibody and Nanobody Design Rubo Wang, Fandi Wu, Xingyu Gao, Jiaxiang Wu, Peilin Zhao, Jianhua Yao

IJCAI 2025 Injecting Imbalance Sensitivity for Multi-Task Learning Zhipeng Zhou, Liu Liu, Peilin Zhao, Wei Gong

ICML 2025 Measuring Diversity in Synthetic Datasets Yuchang Zhu, Huizhe Zhang, Bingzhe Wu, Jintang Li, Zibin Zheng, Peilin Zhao, Liang Chen, Yatao Bian

NeurIPS 2025 Multi-Task Vehicle Routing Solver via Mixture of Specialized Experts Under State-Decomposable MDP Yuxin Pan, Zhiguang Cao, Chengyang Gu, Liu Liu, Peilin Zhao, Yize Chen, Fangzhen Lin

ICML 2025 NTPP: Generative Speech Language Modeling for Dual-Channel Spoken Dialogue via Next-Token-Pair Prediction Qichao Wang, Ziqiao Meng, Wenqian Cui, Yifei Zhang, Pengcheng Wu, Bingzhe Wu, Irwin King, Liang Chen, Peilin Zhao

ICML 2025 Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples Chengqian Gao, Haonan Li, Liu Liu, Zeke Xie, Peilin Zhao, Zhiqiang Xu

NeurIPS 2025 Right Question Is Already Half the Answer: Fully Unsupervised LLM Reasoning Incentivization Qingyang Zhang, Haitao Wu, Changqing Zhang, Peilin Zhao, Yatao Bian

ICLR 2025 Scaling Diffusion Language Models via Adaptation from Autoregressive Models Shansan Gong, Shivam Agarwal, Yizhe Zhang, Jiacheng Ye, Lin Zheng, Mukai Li, Chenxin An, Peilin Zhao, Wei Bi, Jiawei Han, Hao Peng, Lingpeng Kong

ICML 2025 Self-Bootstrapping for Versatile Test-Time Adaptation Shuaicheng Niu, Guohao Chen, Peilin Zhao, Tianyi Wang, Pengcheng Wu, Zhiqi Shen

ICLR 2025 Self-Introspective Decoding: Alleviating Hallucinations for Large Vision-Language Models Fushuo Huo, Wenchao Xu, Zhong Zhang, Haozhao Wang, Zhicheng Chen, Peilin Zhao

AAAI 2025 Spurious Feature Eraser: Stabilizing Test-Time Adaptation for Vision-Language Foundation Model Huan Ma, Yan Zhu, Changqing Zhang, Peilin Zhao, Baoyuan Wu, Long-Kai Huang, Qinghua Hu, Bingzhe Wu

ICLR 2025 TS-LIF: A Temporal Segment Spiking Neuron Network for Time Series Forecasting Feng Shibo, Wanjin Feng, Xingyu Gao, Peilin Zhao, Zhiqi Shen

ICML 2025 Test-Time Adapted Reinforcement Learning with Action Entropy Regularization Shoukai Xu, Zihao Lian, Mingkui Tan, Liu Liu, Zhong Zhang, Peilin Zhao

ICLR 2024 Enhancing Neural Subset Selection: Integrating Background Information into Set Representations Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng

AAAI 2024 Latent Diffusion Transformer for Probabilistic Time Series Forecasting Shibo Feng, Chunyan Miao, Zhong Zhang, Peilin Zhao

ICML 2024 Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations via Pareto Optimization Yichen Wu, Hong Wang, Peilin Zhao, Yefeng Zheng, Ying Wei, Long-Kai Huang

ICLR 2024 Pareto Deep Long-Tailed Recognition: A Conflict-Averse Solution Zhipeng Zhou, Liu Liu, Peilin Zhao, Wei Gong

NeurIPSW 2024 Parrot: Autoregressive Spoken Dialogue Language Modeling with Decoder-Only Transformers Ziqiao Meng, Qichao Wang, Wenqian Cui, Yifei Zhang, Bingzhe Wu, Irwin King, Liang Chen, Peilin Zhao

NeurIPS 2024 SDformer: Similarity-Driven Discrete Transformer for Time Series Generation Zhicheng Chen, Shibo Feng, Zhong Zhang, Xi Xiao, Xingyu Gao, Peilin Zhao

ICLR 2024 SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases Yang Liu, Jiashun Cheng, Haihong Zhao, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li, Yu Rong

ICMLW 2024 Step-on-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping Haoyu Wang, Guozheng Ma, Ziqiao Meng, Zeyu Qin, Li Shen, Zhong Zhang, Bingzhe Wu, Liu Liu, Yatao Bian, Tingyang Xu, Xueqian Wang, Peilin Zhao

ICML 2024 Test-Time Model Adaptation with Only Forward Passes Shuaicheng Niu, Chunyan Miao, Guohao Chen, Pengcheng Wu, Peilin Zhao

IJCAI 2024 Towards Geometric Normalization Techniques in SE(3) Equivariant Graph Neural Networks for Physical Dynamics Simulations Ziqiao Meng, Liang Zeng, Zixing Song, Tingyang Xu, Peilin Zhao, Irwin King

ICLRW 2024 WatME: Towards Lossless Watermarking Through Lexical Redundancy Liang Chen, Yatao Bian, Yang Deng, Deng Cai, Shuaiyi Li, Peilin Zhao, Kam-Fai Wong

ICLR 2023 BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion Fu-Yun Wang, Da-Wei Zhou, Liu Liu, Han-Jia Ye, Yatao Bian, De-Chuan Zhan, Peilin Zhao

IJCAI 2023 A Unified View of Deep Learning for Reaction and Retrosynthesis Prediction: Current Status and Future Challenges Ziqiao Meng, Peilin Zhao, Yang Yu, Irwin King

NeurIPSW 2023 Are Large Language Models Really Robust to Word-Level Perturbations? 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

CVPR 2023 Class-Conditional Sharpness-Aware Minimization for Deep Long-Tailed Recognition Zhipeng Zhou, Lanqing Li, Peilin Zhao, Pheng-Ann Heng, Wei Gong

IJCAI 2023 Doubly Stochastic Graph-Based Non-Autoregressive Reaction Prediction Ziqiao Meng, Peilin Zhao, Yang Yu, Irwin King

AAAI 2023 DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery - A Focus on Affinity Prediction Problems with Noise Annotations 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

TMLR 2023 Dynamics Adapted Imitation Learning Zixuan Liu, Liu Liu, Bingzhe Wu, Lanqing Li, Xueqian Wang, Bo Yuan, Peilin Zhao

NeurIPS 2023 Fairness-Guided Few-Shot Prompting for Large Language Models Huan Ma, Changqing Zhang, Yatao Bian, Lemao Liu, Zhirui Zhang, Peilin Zhao, Shu Zhang, Huazhu Fu, Qinghua Hu, Bingzhe Wu

ICML 2023 FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic Planning Songtao Liu, Zhengkai Tu, Minkai Xu, Zuobai Zhang, Lu Lin, Rex Ying, Jian Tang, Peilin Zhao, Dinghao Wu

NeurIPS 2023 GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection Jianheng Tang, Fengrui Hua, Ziqi Gao, Peilin Zhao, Jia Li

AAAI 2023 Handling Missing Data via Max-Entropy Regularized Graph Autoencoder Ziqi Gao, Yifan Niu, Jiashun Cheng, Jianheng Tang, Lanqing Li, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li

AAAI 2023 ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification Liang Zeng, Lanqing Li, Ziqi Gao, Peilin Zhao, Jian Li

CVPR 2023 On the Pitfall of Mixup for Uncertainty Calibration Deng-Bao Wang, Lanqing Li, Peilin Zhao, Pheng-Ann Heng, Min-Ling Zhang

ICLR 2023 Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Bingzhe Wu, Yonggang Zhang, Ma Kaili, Han Yang, Peilin Zhao, Bo Han, James Cheng

CVPRW 2023 Pareto-Aware Neural Architecture Generation for Diverse Computational Budgets Yong Guo, Yaofo Chen, Yin Zheng, Qi Chen, Peilin Zhao, Junzhou Huang, Jian Chen, Mingkui Tan

NeurIPS 2023 Retaining Beneficial Information from Detrimental Data for Neural Network Repair Long-Kai Huang, Peilin Zhao, Junzhou Huang, Sinno Pan

ICLR 2023 Towards Stable Test-Time Adaptation in Dynamic Wild World Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Zhiquan Wen, Yaofo Chen, Peilin Zhao, Mingkui Tan

ICML 2022 $p$-Laplacian Based Graph Neural Networks Guoji Fu, Peilin Zhao, Yatao Bian

ICML 2022 Efficient Test-Time Model Adaptation Without Forgetting Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Yaofo Chen, Shijian Zheng, Peilin Zhao, Mingkui Tan

AAAI 2022 GNN-Retro: Retrosynthetic Planning with Graph Neural Networks Peng Han, Peilin Zhao, Chan Lu, Junzhou Huang, Jiaxiang Wu, Shuo Shang, Bin Yao, Xiangliang Zhang

LoG 2022 Jointly Modelling Uncertainty and Diversity for Active Molecular Property Prediction Kuangqi Zhou, Kaixin Wang, Jian Tang, Jiashi Feng, Bryan Hooi, Peilin Zhao, Tingyang Xu, Xinchao Wang

NeurIPS 2022 Learning Neural Set Functions Under the Optimal Subset Oracle Zijing Ou, Tingyang Xu, Qinliang Su, Yingzhen Li, Peilin Zhao, Yatao Bian

ICML 2022 Local Augmentation for Graph Neural Networks Songtao Liu, Rex Ying, Hanze Dong, Lanqing Li, Tingyang Xu, Yu Rong, Peilin Zhao, Junzhou Huang, Dinghao Wu

CVPR 2022 SVIP: Sequence VerIfication for Procedures in Videos Yicheng Qian, Weixin Luo, Dongze Lian, Xu Tang, Peilin Zhao, Shenghua Gao

NeurIPS 2022 UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu, Changqing Zhang, Jianhua Yao

AISTATS 2021 Communication Efficient Primal-Dual Algorithm for Nonconvex Nonsmooth Distributed Optimization Congliang Chen, Jiawei Zhang, Li Shen, Peilin Zhao, Zhiquan Luo

ICML 2021 AdaXpert: Adapting Neural Architecture for Growing Data Shuaicheng Niu, Jiaxiang Wu, Guanghui Xu, Yifan Zhang, Yong Guo, Peilin Zhao, Peng Wang, Mingkui Tan

WACV 2021 Context-Aware Domain Adaptation in Semantic Segmentation Jinyu Yang, Weizhi An, Chaochao Yan, Peilin Zhao, Junzhou Huang

ICCV 2021 Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation Jinyu Yang, Chunyuan Li, Weizhi An, Hehuan Ma, Yuzhi Guo, Yu Rong, Peilin Zhao, Junzhou Huang

AAAI 2021 Hierarchical Graph Capsule Network Jinyu Yang, Peilin Zhao, Yu Rong, Chaochao Yan, Chunyuan Li, Hehuan Ma, Junzhou Huang

ICML 2021 Meta-Learning Hyperparameter Performance Prediction with Neural Processes Ying Wei, Peilin Zhao, Junzhou Huang

NeurIPS 2021 Meta-Learning with an Adaptive Task Scheduler Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn

AAAI 2021 PSSM-Distil: Protein Secondary Structure Prediction (PSSP) on Low-Quality PSSM by Knowledge Distillation with Contrastive Learning Qin Wang, Boyuan Wang, Zhenlei Xu, Jiaxiang Wu, Peilin Zhao, Zhen Li, Sheng Wang, Junzhou Huang, Shuguang Cui

NeurIPS 2020 Adversarial Sparse Transformer for Time Series Forecasting Sifan Wu, Xi Xiao, Qianggang Ding, Peilin Zhao, Ying Wei, Junzhou Huang

AAAI 2020 Aggregated Gradient Langevin Dynamics Chao Zhang, Jiahao Xie, Zebang Shen, Peilin Zhao, Tengfei Zhou, Hui Qian

ICML 2020 Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search Yong Guo, Yaofo Chen, Yin Zheng, Peilin Zhao, Jian Chen, Junzhou Huang, Mingkui Tan

IJCAI 2020 Contextualized Point-of-Interest Recommendation Peng Han, Zhongxiao Li, Yong Liu, Peilin Zhao, Jing Li, Hao Wang, Shuo Shang

AAAI 2020 Mastering Complex Control in MOBA Games with Deep Reinforcement Learning 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

IJCAI 2020 Relation-Aware Transformer for Portfolio Policy Learning Ke Xu, Yifan Zhang, Deheng Ye, Peilin Zhao, Mingkui Tan

NeurIPS 2020 RetroXpert: Decompose Retrosynthesis Prediction like a Chemist Chaochao Yan, Qianggang Ding, Peilin Zhao, Shuangjia Zheng, Jinyu Yang, Yang Yu, Junzhou Huang

AAAI 2020 Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks Tian Bian, Xi Xiao, Tingyang Xu, Peilin Zhao, Wenbing Huang, Yu Rong, Junzhou Huang

ICLR 2020 Towards Fast Adaptation of Neural Architectures with Meta Learning Dongze Lian, Yin Zheng, Yintao Xu, Yanxiong Lu, Leyu Lin, Peilin Zhao, Junzhou Huang, Shenghua Gao

AISTATS 2019 Complexities in Projection-Free Stochastic Non-Convex Minimization Zebang Shen, Cong Fang, Peilin Zhao, Junzhou Huang, Hui Qian

AAAI 2019 Confidence Weighted Multitask Learning Peng Yang, Peilin Zhao, Jiayu Zhou, Xin Gao

IJCAI 2019 Decentralized Optimization with Edge Sampling Chi Zhang, Qianxiao Li, Peilin Zhao

NeurIPS 2019 Hyperparameter Learning via Distributional Transfer Ho Chung Law, Peilin Zhao, Leung Sing Chan, Junzhou Huang, Dino Sejdinovic

IJCAI 2019 Margin Learning Embedded Prediction for Video Anomaly Detection with a Few Anomalies Wen Liu, Weixin Luo, Zhengxin Li, Peilin Zhao, Shenghua Gao

NeurIPS 2019 NAT: Neural Architecture Transformer for Accurate and Compact Architectures Yong Guo, Yin Zheng, Mingkui Tan, Qi Chen, Jian Chen, Peilin Zhao, Junzhou Huang

IJCAI 2018 Bandit Online Learning on Graphs via Adaptive Optimization Peng Yang, Peilin Zhao, Xin Gao

MLJ 2018 Distributed Multi-Task Classification: A Decentralized Online Learning Approach Chi Zhang, Peilin Zhao, Shuji Hao, Yeng Chai Soh, Bu-Sung Lee, Chunyan Miao, Steven C. H. Hoi

IJCAI 2018 High-Dimensional Similarity Learning via Dual-Sparse Random Projection Dezhong Yao, Peilin Zhao, Tuan-Anh Nguyen Pham, Gao Cong

AAAI 2018 Privacy Preserving Point-of-Interest Recommendation Using Decentralized Matrix Factorization Chaochao Chen, Ziqi Liu, Peilin Zhao, Jun Zhou, Xiaolong Li

ICML 2018 Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication Zebang Shen, Aryan Mokhtari, Tengfei Zhou, Peilin Zhao, Hui Qian

AAAI 2018 Unified Locally Linear Classifiers with Diversity-Promoting Anchor Points Chenghao Liu, Teng Zhang, Peilin Zhao, Jianling Sun, Steven C. H. Hoi

MLJ 2017 Collaborative Topic Regression for Online Recommender Systems: An Online and Bayesian Approach Chenghao Liu, Tao Jin, Steven C. H. Hoi, Peilin Zhao, Jianling Sun

IJCAI 2017 Learning User Dependencies for Recommendation Yong Liu, Peilin Zhao, Xin Liu, Min Wu, Lixin Duan, Xiaoli Li

IJCAI 2017 Locally Linear Factorization Machines Chenghao Liu, Teng Zhang, Peilin Zhao, Jun Zhou, Jianling Sun

IJCAI 2017 Online Multitask Relative Similarity Learning Shuji Hao, Peilin Zhao, Yong Liu, Steven C. H. Hoi, Chunyan Miao

ICML 2017 Projection-Free Distributed Online Learning in Networks Wenpeng Zhang, Peilin Zhao, Wenwu Zhu, Steven C. H. Hoi, Tong Zhang

ACML 2016 Cost Sensitive Online Multiple Kernel Classification Doyen Sahoo, Steven Hoi, Peilin Zhao

UAI 2016 Efficient Multi-Class Selective Sampling on Graphs Peng Yang, Peilin Zhao, Zhen Hai, Wei Liu, Steven C. H. Hoi, Xiaoli Li

JMLR 2016 Large Scale Online Kernel Learning Jing Lu, Steven C.H. Hoi, Jialei Wang, Peilin Zhao, Zhi-Yong Liu

ICML 2016 Matrix Eigen-Decomposition via Doubly Stochastic Riemannian Optimization Zhiqiang Xu, Peilin Zhao, Jianneng Cao, Xiaoli Li

AAAI 2016 Online ARIMA Algorithms for Time Series Prediction Chenghao Liu, Steven C. H. Hoi, Peilin Zhao, Jianling Sun

MLJ 2016 Online Passive-Aggressive Active Learning Jing Lu, Peilin Zhao, Steven C. H. Hoi

IJCAI 2015 A Boosting Algorithm for Item Recommendation with Implicit Feedback Yong Liu, Peilin Zhao, Aixin Sun, Chunyan Miao

ICML 2015 Adaptive Stochastic Alternating Direction Method of Multipliers Peilin Zhao, Jinwei Yang, Tong Zhang, Ping Li

AAAI 2015 An Adaptive Gradient Method for Online AUC Maximization Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong

IJCAI 2015 Online Learning to Rank for Content-Based Image Retrieval Ji Wan, Pengcheng Wu, Steven C. H. Hoi, Peilin Zhao, Xingyu Gao, Dayong Wang, Yongdong Zhang, Jintao Li

ICML 2015 Stochastic Optimization with Importance Sampling for Regularized Loss Minimization Peilin Zhao, Tong Zhang

MLOSS 2014 LIBOL: A Library for Online Learning Algorithms Steven C.H. Hoi, Jialei Wang, Peilin Zhao

AAAI 2014 Learning Relative Similarity by Stochastic Dual Coordinate Ascent Pengcheng Wu, Yi Ding, Peilin Zhao, Chunyan Miao, Steven C. H. Hoi

ACML 2014 Online Passive Aggressive Active Learning and Its Applications Jing Lu, Peilin Zhao, Steven Hoi

UAI 2013 Active Learning with Expert Advice Peilin Zhao, Steven C. H. Hoi, Jinfeng Zhuang

IJCAI 2013 Large Scale Online Kernel Classification Steven C. H. Hoi, Jialei Wang, Peilin Zhao, Jinfeng Zhuang, Zhiyong Liu

MLJ 2013 Online Multiple Kernel Classification Steven C. H. Hoi, Rong Jin, Peilin Zhao, Tianbao Yang

ECML-PKDD 2012 BDUOL: Double Updating Online Learning on a Fixed Budget Peilin Zhao, Steven C. H. Hoi

ICML 2012 Exact Soft Confidence-Weighted Learning Steven C. H. Hoi, Jialei Wang, Peilin Zhao

ICML 2012 Fast Bounded Online Gradient Descent Algorithms for Scalable Kernel-Based Online Learning Steven C. H. Hoi, Jialei Wang, Peilin Zhao, Rong Jin, Pengcheng Wu

MLJ 2012 PAMR: Passive Aggressive Mean Reversion Strategy for Portfolio Selection Bin Li, Peilin Zhao, Steven C. H. Hoi, Vivekanand Gopalkrishnan

AISTATS 2011 Confidence Weighted Mean Reversion Strategy for On-Line Portfolio Selection Bin Li, Steven C.H. Hoi, Peilin Zhao, Vivekanand Gopalkrishnan

JMLR 2011 Double Updating Online Learning Peilin Zhao, Steven C.H. Hoi, Rong Jin

ICML 2011 Online AUC Maximization Peilin Zhao, Steven C. H. Hoi, Rong Jin, Tianbao Yang

CVPR 2010 Local Features Are Not Lonely - Laplacian Sparse Coding for Image Classification Shenghua Gao, Ivor Wai-Hung Tsang, Liang-Tien Chia, Peilin Zhao

ICML 2010 OTL: A Framework of Online Transfer Learning Peilin Zhao, Steven C. H. Hoi

NeurIPS 2009 DUOL: A Double Updating Approach for Online Learning Peilin Zhao, Steven C. Hoi, Rong Jin