MSR Asia Theory Center

Publications

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- Embedding-Space Orthogonal Decomposition for Robust Social Recommendation
  
  Rongfeng Guo, Yinxuan Huang, Wei Chen, Mingyang Zhou, Yusen Wu, Yangchen Zeng, Han Chen, Hao Liao
  
  2026 the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) | August 2026
  
  PDF
- PaT: Planning-after-Trial for Efficient Test-Time Code Generation
  
  Youngsik Yoon, Sungjae Lee, Seockbean Song, Siwei Wang, Wei Chen, Jungseul Ok
  
  The 64th Annual Meeting of the Association for Computational Linguistics (ACL), Main Conference | July 2026
  
  PDF
- Toward Consistent World Models with Multi-Token Prediction and Latent Semantic Enhancement
  
  Qimin Zhong, Hao Liao, Haiming Qin, Mingyang Zhou, Rui Mao, Wei Chen, Naipeng Chao
  
  The 64th Annual Meeting of the Association for Computational Linguistics (ACL), Main Conference | July 2026
  
  Publication
- Semantic Caching for Low-Cost LLM Serving: From Offline Learning to Online Adaptation
  
  Xutong Liu, Baran Atalar, Xiangxiang Dai, Jinhang Zuo, Siwei Wang, John C.S. Lui, Wei Chen, Carlee Joe-Wong
  
  IEEE International Conference on Computer Communications (INFOCOM) | May 2026
  
  PDF Preprint
- Benefits and Pitfalls of Reinforcement Learning for Language Model Planning: A Theoretical Perspective
  
  Siwei Wang, Yifei Shen, Haoran Sun, Shi Feng, Shang-Hua Teng, Li Dong, Yaru Hao, Wei Chen
  
  The 14th International Conference on Learning Representations (ICLR) | April 2026
  
  PDF DOI Publication
- Combinatorial Rising Bandits
  
  Seockbean Song, Youngsik Yoon, Siwei Wang, Wei Chen, Jungseul Ok
  
  The 14th International Conference on Learning Representations (ICLR) | April 2026
  
  PDF Preprint
- Latent-DARM: Bridging Discrete Diffusion and Autoregressive Models for Reasoning
  
  Lina Berrayana, Ahmed Heakl, Muhammad Abdullah Sohail, Thomas Hofmann, Salman Khan, Wei Chen
  
  Proceedings of Workshop on Latent & Implicit Thinking – Going Beyond CoT Reasoning (LIT), the 14th International Conference on Learning Representations (ICLR) | April 2026
  
  PDF Preprint
- Mechanism Design for LLM Fine-tuning with Multiple Reward Models
  
  Haoran Sun, Yurong Chen, Siwei Wang, Xu Chu, Wei Chen, Xiaotie Deng
  
  Neural Information Processing Systems (NeurIPS) 2025 | December 2025
  
  PDF
- Offline Learning for Combinatorial Multi-armed Bandits
  
  Xutong Liu, Xiangxiang Dai, Jinhang Zuo, Siwei Wang, Carlee Joe-Wong, John C.S. Lui, Wei Chen
  
  Proceedings of the 42nd International Conference on Machine Learning (ICML) | July 2025
  
  PDF
- A Scalable Algorithm for Fair Influence Maximization with Unbiased Estimator
  
  Xiaobin Rui, Zhixiao Wang, Hao Peng, Wei Chen, Philip S. Yu
  
  IEEE Transactions on Knowledge and Data Engineering (TKDE) | May 2025
  
  PDF
- Structural-Entropy-Based Sample Selection for Efficient and Effective Learning
  
  Tianchi Xie, Jiangning Zhu, Guozu Ma, Minzhi Lin, Wei Chen, Weikai Yang, Shixia Liu
  
  Proceedings of the 13th International Conference on Learning Representations (ICLR) | April 2025
  
  PDF
- Combinatorial Causal Bandits without Graph Skeleton
  
  Shi Feng, Nuoya Xiong, Wei Chen
  
  Proceedings of the 16th Asian Conference on Machine Learning (ACML) | December 2024
  
  PDF
- Convergence to Equilibrium of No-regret Dynamics in Congestion Games
  
  Volkan Cevher, Wei Chen, Leello Dadi, Jing Dong, Ioannis Panageas, Stratis Skoulakis, Luca Viano, Baoxiang Wang, Siwei Wang, Jingyu Wu
  
  Conference on Web and Internet Economics (WINE) | December 2024
  
  PDF Publication
- Query-Efficient Correlation Clustering with Noisy Oracle
  
  Yuko Kuroki, Atsushi Miyauchi, Francesco Bonchi, Wei Chen
  
  NeurIPS 2024 | December 2024
  
  PDF DOI
- Uncovering Milestone Papers: A Network Diffusion and Game Theory Approach
  
  Wei Zhang, Juyang Cao, Manuel Sebastian Mariani, Zhen-Zhen Wang, Mingyang Zhou, Wei Chen, Hao Liao
  
  Journal of Informetrics | August 2024, Vol 18(3)
  
  Publication
- Combinatorial Multivariant Multi-Armed Bandits with Applications to Episodic Reinforcement Learning and Beyond
  
  Xutong Liu, Siwei Wang, Jinhang Zuo, Han Zhong, Xuchuang Wang, Zhiyong Wang, Shuai Li, Mohammad Hajiesmaili, John C.S. Lui, Wei Chen
  
  Proceedings of the 41st International Conference on Machine Learning (ICML) | July 2024
  
  PDF
- Cascading Reinforcement Learning
  
  Yihan Du, R. Srikant, Wei Chen
  
  Proceedings of the 12th International Conference on Learning Representations (ICLR) | May 2024
  
  PDF
- Combinatorial Bandits for Maximum Value Reward Function under Value-index Feedback
  
  Yiliu Wang, Wei Chen, Milan Vojnovic
  
  Proceedings of the 12th International Conference on Learning Representations (ICLR) | May 2024
  
  PDF
- Selective Pre-training for Private Fine-tuning
  
  Da Yu, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Zinan Lin, Saurabh Naik, Tomasz Lukasz Religa, Jian Yin, Huishuai Zhang
  
  TMLR | May 2024
  
  Publication Publication Project
- Scalable Fair Influence Maximization
  
  Xiaobin Rui, Zhixiao Wang, Jiayu Zhao, Lichao Sun, Wei Chen
  
  Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS) | December 2023
  
  PDF Preprint
- Mitigating Filter Bubbles Under a Competitive Diffusion Model
  
  Prithu Banerjee, Wei Chen, Laks V.S. Lakshmanan
  
  Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD) | June 2023
  
  PDF
- Popularity Ratio Maximization: Surpassing Competitors through Influence Propagation
  
  Hao Liao, Sheng Bi, Jiao Wu, Wei Zhang, Mingyang Zhou, Rui Mao, Wei Chen
  
  Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD) | June 2023
  
  PDF
- Collaborative Pure Exploration in Kernel Bandit
  
  Yihan Du, Wei Chen, Yuko Kuroki, Longbo Huang
  
  Proceedings of the 11th International Conference on Learning Representations (ICLR) | May 2023
  
  PDF
- Combinatorial Pure Exploration of Causal Bandits
  
  Nuoya Xiong, Wei Chen
  
  Proceedings of the 11th International Conference on Learning Representations (ICLR) | May 2023
  
  PDF
- Denoising Masked Auto-encoders Helps Robust Classification
  
  QuanLin Wu, Hang Ye, Yuntian Gu, Huishuai Zhang, Liwei Wang, Di He
  
  International Conference on Learning Representations (ICLR) 2023 | May 2023
  
  Publication
- Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
  
  Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan (Jana) Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian
  
  International Conference on Learning Representations (ICLR) 2023 | May 2023
  
  Publication Project
- Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks
  
  Huishuai Zhang, Da Yu, Yiping Lu, Di He
  
  International Conference on Artificial Intelligence and Statistics (AIStats) | April 2023
  
  Preprint
- Combinatorial Causal Bandits
  
  Shi Feng, Wei Chen
  
  Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI) | February 2023
  
  PDF Preprint
- Scalable Adversarial Attack Algorithms on Influence Maximization
  
  Lichao Sun, Xiaobin Rui, Wei Chen
  
  Proceedings of the 16th ACM International WSDM Conference (WSDM) | February 2023
  
  PDF Preprint
- Does Momentum Change the Implicit Regularization on Separable Data?
  
  Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
  
  NeurIPS 2022 | November 2022
  
  Publication
- Batch-Size Independent Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms or Independent Arms
  
  Xutong Liu, Jinhang Zuo, Siwei Wang, Carlee Joe-Wong, John C.S. Lui, Wei Chen
  
  Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS) | November 2022
  
  PDF
- Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret
  
  Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu
  
  Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS) | November 2022
  
  PDF
- Stabilize Deep ResNet with A Sharp Scaling Factor τ
  
  Huishuai Zhang, Da Yu, Mingyang Yi, Wei Chen, Tie-Yan Liu
  
  Machine Learning | September 2022
  
  Publication Publication
- Availability attacks create shortcuts
  
  Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu, Jian Yin
  
  Knowledge Discovery and Data Mining | August 2022
  
  Publication
- The pure exploration problem with general reward functions depending on full distributions
  
  Siwei Wang, Wei Chen
  
  Machine Learning | July 2022
  
  Publication
- Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum
  
  Zeke Xie, Xinrui Wang, Huishuai Zhang, Issei Sato, Masashi Sugiyama
  
  ICML 2022 | July 2022
  
  Publication
- Branching Reinforcement Learning
  
  Yihan Du, Wei Chen
  
  Proceedings of the 39th International Conference on Machine Learning (ICML) | July 2022
  
  PDF Preprint
- Adaptive Greedy versus Non-Adaptive Greedy for Influence Maximization
  
  Wei Chen, Binghui Peng, Grant Schoenebeck, Biaoshuai Tao
  
  Journal of Artificial Intelligence Research | May 2022, Vol 74: pp. 303-351
  
  PDF
- Differentially private fine-tuning of language models
  
  Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Gautam Kamath, Janardhan (Jana) Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang
  
  ICLR 2022 | April 2022
  
  Publication Project
- Gradient Information Matters in Policy Optimization by Back-propagating through Model
  
  Chongchong Li, Yue Wang, Wei Chen, Yuting Liu, Zhi-Ming Ma, Tie-Yan Liu
  
  ICLR 2022 | April 2022
  
  Publication
- PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior
  
  Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu
  
  ICLR 2022 | April 2022
  
  Publication
- Online Competitive Influence Maximization
  
  Jinhang Zuo, Xutong Liu, Carlee Joe-Wong, John C.S. Lui, Wei Chen
  
  Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS) | March 2022
  
  PDF
- Online Influence Maximization under the Independent Cascade Model with Node-Level Feedback
  
  Zhijie Zhang, Wei Chen, Xiaoming Sun, Jialin Zhang
  
  Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI) | February 2022
  
  This version fixed some bugs contained in the published version. See footnote in the first page.
  
  PDF
- Higher Order Monotonicity and Submodularity of Influence in Social Networks: From Local to Global
  
  Wei Chen, Qiang Li, Xiaohan Shan, Xiaoming Sun, Jialin Zhang
  
  Information and Computation | January 2022
  
  PDF
- Combinatorial Pure Exploration with Bottleneck Reward Function
  
  Yihan Du, Yuko Kuroki, Wei Chen
  
  Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS) | December 2021
  
  PDF Publication
- Learning Causal Semantic Representation for Out-of-Distribution Prediction
  
  Chang Liu, Xinwei Sun, Jindong Wang, Haoyue Tang, Tao Li, Tao Qin, Wei Chen, Tie-Yan Liu
  
  NeurIPS 2021 | December 2021
  
  Publication
- Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD
  
  Bohan Wang, Huishuai Zhang, Jieyu Zhang, Qi Meng, Wei Chen, Tie-Yan Liu
  
  NeurIPS 2021 | December 2021
  
  Publication
- R-Drop: Regularized Dropout for Neural Networks
  
  xiaobo liang, Lijun Wu, Juntao Li, Yue Wang, Qi Meng, Tao Qin, Wei Chen, Min Zhang, Tie-Yan Liu
  
  NeurIPS 2021 | December 2021
  
  Publication
- Recovering Latent Causal Factor for Generalization to Distributional Shifts
  
  Xinwei Sun, Botong Wu, Xiangyu Zheng, Chang Liu, Wei Chen, Tao Qin, Tie-Yan Liu
  
  NeurIPS 2021 | December 2021
  
  Publication
- The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle
  
  Fang Kong, Yueran Yang, Wei Chen, Shuai Li
  
  Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS) | December 2021
  
  PDF Publication
- Causal Inference for Influence Propagation — Identifiability of the Independent Cascade Model
  
  Shi Feng, Wei Chen
  
  Proceedings of the 10th International Conference on Computational Social Networks (CSoNet’2021) | November 2021
  
  Winner of the sole Best Paper Award
  
  PDF
- 基于优化反馈的组合在线学习 (Combinatorial Online Learning Based on Optimizing feedbacks）
  
  Fang Kong, Yueran Yang, Wei Chen, Shuai Li
  
  大数据（Big Data Research） | September 2021, Vol 7(5)
  
  PDF
- 基于样本的优化（Optimization from Samples）
  
  Zhijie Zhang, Xiaoming Sun, Jialin Zhang, Wei Chen
  
  大数据（Big Data Research） | September 2021, Vol 7(5): pp. 100-110
  
  PDF
- Contextual Bandit Applications in a Customer Support Bot
  
  Sandra Sajeev, Jade Huang, Nikos Karampatziakis, Sebastian Kochman, Matthew Hall, Wei Chen
  
  KDD 2021 | August 2021
  
  Publication Publication
- Maximizing Social Welfare in a Competitive Diffusion Model
  
  Prithu Banerjee, Wei Chen, Laks V.S. Lakshmanan
  
  VLDB 2021 | August 2021
  
  PDF Publication
- Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning
  
  Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui
  
  2021 International Conference on Machine Learning (ICML) | July 2021
  
  PDF Publication
- Poolingformer: Long Document Modeling with Pooling Attention
  
  Hang Zhang, Yeyun Gong, Yelong Shen, Weisheng Li, Jiancheng Lv, Nan Duan, Wei Chen
  
  2021 International Conference on Machine Learning | July 2021
  
  Publication Publication
- The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks
  
  Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu
  
  2021 International Conference on Machine Learning | July 2021
  
  Publication
- Large Scale Private Learning via Low-rank Reparametrization
  
  Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
  
  International Conference on Machine Learning (ICML) | July 2021
  
  PDF
- Network Inference and Influence Maximization from Samples
  
  Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
  
  2021 International Conference on Machine Learning (ICML) | July 2021
  
  PDF Publication
- Combinatorial Semi-Bandit in the Non-Stationary Environment
  
  Wei Chen, Liwei Wang, Haoyu Zhao, Kai Zheng
  
  Conference on Uncertainty in Artificial Intelligence (UAI) 2021 | June 2021
  
  PDF Publication
- Path-BN: Towards Effective Batch Normalization in the Path Space for ReLU Networks
  
  Xufang Luo, Qi Meng, Wei Chen, Tie-Yan Liu
  
  June 2021
- Memory-Efficient Differentiable Transformer Architecture Search
  
  Yuekai Zhao, Li Dong, Yelong Shen, Zhihua Zhang, Furu Wei, Wei Chen
  
  ACL-IJCNLP 2021 | May 2021
  
  Publication
- Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization
  
  Chen Liang, Simiao Zuo, Minshuo Chen, Haoming Jiang, Xiaodong Liu, Pengcheng He, Tuo Zhao, Wei Chen
  
  ACL-IJCNLP 2021 | May 2021
  
  Publication
- DeBERTa: Decoding-Enhanced BERT with Disentangled Attention
  
  Pengcheng He, Xiaodong Liu, Jianfeng Gao, Wei Chen
  
  2021 International Conference on Learning Representations | May 2021
  
  Under review
  
  PDF Publication Github Project Project
- Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning
  
  Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu
  
  ICLR 2021 | May 2021
  
  Publication
- Token-wise Curriculum Learning for Neural Machine Translation
  
  Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Wei Chen, Jianfeng Gao, Tuo Zhao
  
  Empirical Methods in Natural Language Processing | March 2021
  
  Publication
- Combinatorial Pure Exploration with Full-Bandit or Partial Linear Feedback
  
  Yihan Du, Yuko Kuroki, Wei Chen
  
  Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI) | February 2021
  
  PDF
- How Does Data Augmentation Affect Privacy in Machine Learning?
  
  Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
  
  AAAI 2021 | January 2021
  
  Publication
- BANG: Bridging Autoregressive and Non-autoregressive Generation with Large Scale Pretraining
  
  Weizhen Qi, Yeyun Gong, Jian Jiao, Yu Yan, Dayiheng Liu, Wei Chen, Kewen Tang, Houqiang Li, Jiusheng Chen, Ruofei Zhang, Ming Zhou, Nan Duan
  
  2021 International Conference on Machine Learning | December 2020
  
  Publication
- Online Influence Maximization under Linear Threshold Model
  
  Shuai Li, Fang Kong, Kejie Tang, Qizhi Li, Wei Chen
  
  Proceedings of the 33rd Conference on Neural Information Processing Systems (NeurIPS) | December 2020
  
  Some typos in the original NeurIPS'2020 paper have been fixed.
  
  PDF
- GLGE: A New General Language Generation Evaluation Benchmark
  
  Dayiheng Liu, Yu Yan, Yeyun Gong, Weizhen Qi, Hang Zhang, Jian Jiao, Wei Chen, Jie Fu, Linjun Shou, Ming Gong (YIMING), Pengcheng Wang, Jiusheng Chen, Daxin Jiang (姜大昕), Jiancheng Lv, Ruofei Zhang, Winnie Wu, Ming Zhou, Nan Duan
  
  ACL-IJCNLP 2021 | November 2020
  
  Publication Access
- Target Transfer Q-learning and Its Convergence Analysis
  
  Yue Wang, Yuting Liu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
  
  Neurocomputing | June 2020
- Thompson Sampling for Combinatorial Semi-Bandits
  
  Siwei Wang, Wei Chen
  
  Proceedings of the 35th International Conference on Machine Learning (ICML’2018) | July 2018
  
  PDF
- Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting
  
  Yue Wang, Wei Chen, Yuting Liu, Zhi-Ming Ma, Tie-Yan Liu
  
  Advances in Neural Information Processing Systems | December 2017
  
  Publication
- Combinatorial Pure Exploration of Multi-Armed Bandits
  
  Shouyuan Chen, Tian Lin, Irwin King, Michael R. Lyu, Wei Chen
  
  Proceedings of the 28th Annual Conference on Advances in Neural Information Processing Systems (NIPS’2014) | December 2014
  
  The PDF download link contains some bug fixes to the original paper.
  
  PDF
- Influence Maximization in Social Networks When Negative Opinions May Emerge and Propagate
  
  Wei Chen, Alex Collins, Rachel Cummings, Te Ke, Zhenming Liu, David Rincon, Xiaorui Sun, Wei Wei, Yajun Wang, Yifei Yuan
  
  Proceedings of the 11th SIAM International Conference on Data Mining (SDM) | April 2011
  
  PDF Preprint

- Embedding-Space Orthogonal Decomposition for Robust Social Recommendation
  
  Rongfeng Guo, Yinxuan Huang, Wei Chen, Mingyang Zhou, Yusen Wu, Yangchen Zeng, Han Chen, Hao Liao
  
  2026 the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) | August 2026
  
  PDF
- PaT: Planning-after-Trial for Efficient Test-Time Code Generation
  
  Youngsik Yoon, Sungjae Lee, Seockbean Song, Siwei Wang, Wei Chen, Jungseul Ok
  
  The 64th Annual Meeting of the Association for Computational Linguistics (ACL), Main Conference | July 2026
  
  PDF
- Semantic Caching for Low-Cost LLM Serving: From Offline Learning to Online Adaptation
  
  Xutong Liu, Baran Atalar, Xiangxiang Dai, Jinhang Zuo, Siwei Wang, John C.S. Lui, Wei Chen, Carlee Joe-Wong
  
  IEEE International Conference on Computer Communications (INFOCOM) | May 2026
  
  PDF Preprint
- Latent-DARM: Bridging Discrete Diffusion and Autoregressive Models for Reasoning
  
  Lina Berrayana, Ahmed Heakl, Muhammad Abdullah Sohail, Thomas Hofmann, Salman Khan, Wei Chen
  
  Proceedings of Workshop on Latent & Implicit Thinking – Going Beyond CoT Reasoning (LIT), the 14th International Conference on Learning Representations (ICLR) | April 2026
  
  PDF Preprint
- Combinatorial Rising Bandits
  
  Seockbean Song, Youngsik Yoon, Siwei Wang, Wei Chen, Jungseul Ok
  
  The 14th International Conference on Learning Representations (ICLR) | April 2026
  
  PDF Preprint
- Benefits and Pitfalls of Reinforcement Learning for Language Model Planning: A Theoretical Perspective
  
  Siwei Wang, Yifei Shen, Haoran Sun, Shi Feng, Shang-Hua Teng, Li Dong, Yaru Hao, Wei Chen
  
  The 14th International Conference on Learning Representations (ICLR) | April 2026
  
  PDF DOI Publication
- Mechanism Design for LLM Fine-tuning with Multiple Reward Models
  
  Haoran Sun, Yurong Chen, Siwei Wang, Xu Chu, Wei Chen, Xiaotie Deng
  
  Neural Information Processing Systems (NeurIPS) 2025 | December 2025
  
  PDF
- Offline Learning for Combinatorial Multi-armed Bandits
  
  Xutong Liu, Xiangxiang Dai, Jinhang Zuo, Siwei Wang, Carlee Joe-Wong, John C.S. Lui, Wei Chen
  
  Proceedings of the 42nd International Conference on Machine Learning (ICML) | July 2025
  
  PDF
- A Scalable Algorithm for Fair Influence Maximization with Unbiased Estimator
  
  Xiaobin Rui, Zhixiao Wang, Hao Peng, Wei Chen, Philip S. Yu
  
  IEEE Transactions on Knowledge and Data Engineering (TKDE) | May 2025
  
  PDF
- Structural-Entropy-Based Sample Selection for Efficient and Effective Learning
  
  Tianchi Xie, Jiangning Zhu, Guozu Ma, Minzhi Lin, Wei Chen, Weikai Yang, Shixia Liu
  
  Proceedings of the 13th International Conference on Learning Representations (ICLR) | April 2025
  
  PDF
- Convergence to Equilibrium of No-regret Dynamics in Congestion Games
  
  Volkan Cevher, Wei Chen, Leello Dadi, Jing Dong, Ioannis Panageas, Stratis Skoulakis, Luca Viano, Baoxiang Wang, Siwei Wang, Jingyu Wu
  
  Conference on Web and Internet Economics (WINE) | December 2024
  
  PDF Publication
- Combinatorial Causal Bandits without Graph Skeleton
  
  Shi Feng, Nuoya Xiong, Wei Chen
  
  Proceedings of the 16th Asian Conference on Machine Learning (ACML) | December 2024
  
  PDF
- Query-Efficient Correlation Clustering with Noisy Oracle
  
  Yuko Kuroki, Atsushi Miyauchi, Francesco Bonchi, Wei Chen
  
  NeurIPS 2024 | December 2024
  
  PDF DOI
- Uncovering Milestone Papers: A Network Diffusion and Game Theory Approach
  
  Wei Zhang, Juyang Cao, Manuel Sebastian Mariani, Zhen-Zhen Wang, Mingyang Zhou, Wei Chen, Hao Liao
  
  Journal of Informetrics | August 2024, Vol 18(3)
  
  Publication
- Combinatorial Multivariant Multi-Armed Bandits with Applications to Episodic Reinforcement Learning and Beyond
  
  Xutong Liu, Siwei Wang, Jinhang Zuo, Han Zhong, Xuchuang Wang, Zhiyong Wang, Shuai Li, Mohammad Hajiesmaili, John C.S. Lui, Wei Chen
  
  Proceedings of the 41st International Conference on Machine Learning (ICML) | July 2024
  
  PDF
- Combinatorial Bandits for Maximum Value Reward Function under Value-index Feedback
  
  Yiliu Wang, Wei Chen, Milan Vojnovic
  
  Proceedings of the 12th International Conference on Learning Representations (ICLR) | May 2024
  
  PDF
- Cascading Reinforcement Learning
  
  Yihan Du, R. Srikant, Wei Chen
  
  Proceedings of the 12th International Conference on Learning Representations (ICLR) | May 2024
  
  PDF
- Selective Pre-training for Private Fine-tuning
  
  Da Yu, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Zinan Lin, Saurabh Naik, Tomasz Lukasz Religa, Jian Yin, Huishuai Zhang
  
  TMLR | May 2024
  
  Publication Publication Project
- Scalable Fair Influence Maximization
  
  Xiaobin Rui, Zhixiao Wang, Jiayu Zhao, Lichao Sun, Wei Chen
  
  Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS) | December 2023
  
  PDF Preprint
- Mitigating Filter Bubbles Under a Competitive Diffusion Model
  
  Prithu Banerjee, Wei Chen, Laks V.S. Lakshmanan
  
  Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD) | June 2023
  
  PDF
- Popularity Ratio Maximization: Surpassing Competitors through Influence Propagation
  
  Hao Liao, Sheng Bi, Jiao Wu, Wei Zhang, Mingyang Zhou, Rui Mao, Wei Chen
  
  Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD) | June 2023
  
  PDF
- Collaborative Pure Exploration in Kernel Bandit
  
  Yihan Du, Wei Chen, Yuko Kuroki, Longbo Huang
  
  Proceedings of the 11th International Conference on Learning Representations (ICLR) | May 2023
  
  PDF
- Combinatorial Pure Exploration of Causal Bandits
  
  Nuoya Xiong, Wei Chen
  
  Proceedings of the 11th International Conference on Learning Representations (ICLR) | May 2023
  
  PDF
- Denoising Masked Auto-encoders Helps Robust Classification
  
  QuanLin Wu, Hang Ye, Yuntian Gu, Huishuai Zhang, Liwei Wang, Di He
  
  International Conference on Learning Representations (ICLR) 2023 | May 2023
  
  Publication
- Combinatorial Causal Bandits
  
  Shi Feng, Wei Chen
  
  Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI) | February 2023
  
  PDF Preprint
- Scalable Adversarial Attack Algorithms on Influence Maximization
  
  Lichao Sun, Xiaobin Rui, Wei Chen
  
  Proceedings of the 16th ACM International WSDM Conference (WSDM) | February 2023
  
  PDF Preprint
- Batch-Size Independent Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms or Independent Arms
  
  Xutong Liu, Jinhang Zuo, Siwei Wang, Carlee Joe-Wong, John C.S. Lui, Wei Chen
  
  Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS) | November 2022
  
  PDF
- Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret
  
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  Journal of Artificial Intelligence Research | May 2022, Vol 74: pp. 303-351
  
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  Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS) | March 2022
  
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  Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI) | February 2022
  
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  Proceedings of the 10th International Conference on Computational Social Networks (CSoNet’2021) | November 2021
  
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  大数据（Big Data Research） | September 2021, Vol 7(5)
  
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  大数据（Big Data Research） | September 2021, Vol 7(5): pp. 100-110
  
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  ACL-IJCNLP 2021 | May 2021
  
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  Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI) | February 2021
  
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- Online Influence Maximization under Linear Threshold Model
  
  Shuai Li, Fang Kong, Kejie Tang, Qizhi Li, Wei Chen
  
  Proceedings of the 33rd Conference on Neural Information Processing Systems (NeurIPS) | December 2020
  
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  Neurocomputing | June 2020
- Thompson Sampling for Combinatorial Semi-Bandits
  
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  Proceedings of the 35th International Conference on Machine Learning (ICML’2018) | July 2018
  
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  Advances in Neural Information Processing Systems | December 2017
  
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  Proceedings of the 28th Annual Conference on Advances in Neural Information Processing Systems (NIPS’2014) | December 2014
  
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  Proceedings of the 11th SIAM International Conference on Data Mining (SDM) | April 2011
  
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  2026 the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) | August 2026
  
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  Youngsik Yoon, Sungjae Lee, Seockbean Song, Siwei Wang, Wei Chen, Jungseul Ok
  
  The 64th Annual Meeting of the Association for Computational Linguistics (ACL), Main Conference | July 2026
  
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  The 64th Annual Meeting of the Association for Computational Linguistics (ACL), Main Conference | July 2026
  
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  IEEE International Conference on Computer Communications (INFOCOM) | May 2026
  
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  Proceedings of Workshop on Latent & Implicit Thinking – Going Beyond CoT Reasoning (LIT), the 14th International Conference on Learning Representations (ICLR) | April 2026
  
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  The 14th International Conference on Learning Representations (ICLR) | April 2026
  
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  The 14th International Conference on Learning Representations (ICLR) | April 2026
  
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  Neural Information Processing Systems (NeurIPS) 2025 | December 2025
  
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  Proceedings of the 42nd International Conference on Machine Learning (ICML) | July 2025
  
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  IEEE Transactions on Knowledge and Data Engineering (TKDE) | May 2025
  
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  NeurIPS 2024 | December 2024
  
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  Proceedings of the 41st International Conference on Machine Learning (ICML) | July 2024
  
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  Proceedings of the 12th International Conference on Learning Representations (ICLR) | May 2024
  
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  Proceedings of the 12th International Conference on Learning Representations (ICLR) | May 2024
  
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  Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS) | December 2023
  
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  Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD) | June 2023
  
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  Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD) | June 2023
  
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  Yihan Du, Wei Chen, Yuko Kuroki, Longbo Huang
  
  Proceedings of the 11th International Conference on Learning Representations (ICLR) | May 2023
  
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  Proceedings of the 11th International Conference on Learning Representations (ICLR) | May 2023
  
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  Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI) | February 2023
  
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  Proceedings of the 16th ACM International WSDM Conference (WSDM) | February 2023
  
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  NeurIPS 2022 | November 2022
  
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  Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS) | November 2022
  
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  Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS) | November 2022
  
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  Proceedings of the 39th International Conference on Machine Learning (ICML) | July 2022
  
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  Wei Chen, Binghui Peng, Grant Schoenebeck, Biaoshuai Tao
  
  Journal of Artificial Intelligence Research | May 2022, Vol 74: pp. 303-351
  
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- Online Influence Maximization under the Independent Cascade Model with Node-Level Feedback
  
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  Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI) | February 2022
  
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  Proceedings of the 10th International Conference on Computational Social Networks (CSoNet’2021) | November 2021
  
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  大数据（Big Data Research） | September 2021, Vol 7(5)
  
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- 基于样本的优化（Optimization from Samples）
  
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  大数据（Big Data Research） | September 2021, Vol 7(5): pp. 100-110
  
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  KDD 2021 | August 2021
  
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  International Conference on Machine Learning (ICML) | July 2021
  
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  Prithu Banerjee, Wei Chen, Laks V.S. Lakshmanan
  
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  Shuai Li, Fang Kong, Kejie Tang, Qizhi Li, Wei Chen
  
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  Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD) | June 2023
  
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- Online Influence Maximization under the Independent Cascade Model with Node-Level Feedback
  
  Zhijie Zhang, Wei Chen, Xiaoming Sun, Jialin Zhang
  
  Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI) | February 2022
  
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  Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui
  
  2021 International Conference on Machine Learning (ICML) | July 2021
  
  PDF Publication
- Network Inference and Influence Maximization from Samples
  
  Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
  
  2021 International Conference on Machine Learning (ICML) | July 2021
  
  PDF Publication
- Mechanism Design for LLM Fine-tuning with Multiple Reward Models
  
  Haoran Sun, Yurong Chen, Siwei Wang, Xu Chu, Wei Chen, Xiaotie Deng
  
  Neural Information Processing Systems (NeurIPS) 2025 | December 2025
  
  PDF
- Convergence to Equilibrium of No-regret Dynamics in Congestion Games
  
  Volkan Cevher, Wei Chen, Leello Dadi, Jing Dong, Ioannis Panageas, Stratis Skoulakis, Luca Viano, Baoxiang Wang, Siwei Wang, Jingyu Wu
  
  Conference on Web and Internet Economics (WINE) | December 2024
  
  PDF Publication
- Selective Pre-training for Private Fine-tuning
  
  Da Yu, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Zinan Lin, Saurabh Naik, Tomasz Lukasz Religa, Jian Yin, Huishuai Zhang
  
  TMLR | May 2024
  
  Publication Publication Project
- Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
  
  Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan (Jana) Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian
  
  International Conference on Learning Representations (ICLR) 2023 | May 2023
  
  Publication Project
- Denoising Masked Auto-encoders Helps Robust Classification
  
  QuanLin Wu, Hang Ye, Yuntian Gu, Huishuai Zhang, Liwei Wang, Di He
  
  International Conference on Learning Representations (ICLR) 2023 | May 2023
  
  Publication
- Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks
  
  Huishuai Zhang, Da Yu, Yiping Lu, Di He
  
  International Conference on Artificial Intelligence and Statistics (AIStats) | April 2023
  
  Preprint
- Availability attacks create shortcuts
  
  Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu, Jian Yin
  
  Knowledge Discovery and Data Mining | August 2022
  
  Publication
- Large Scale Private Learning via Low-rank Reparametrization
  
  Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
  
  International Conference on Machine Learning (ICML) | July 2021
  
  PDF
- Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning
  
  Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu
  
  ICLR 2021 | May 2021
  
  Publication
- How Does Data Augmentation Affect Privacy in Machine Learning?
  
  Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
  
  AAAI 2021 | January 2021
  
  Publication
- Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization
  
  Chen Liang, Simiao Zuo, Minshuo Chen, Haoming Jiang, Xiaodong Liu, Pengcheng He, Tuo Zhao, Wei Chen
  
  ACL-IJCNLP 2021 | May 2021
  
  Publication
- Token-wise Curriculum Learning for Neural Machine Translation
  
  Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Wei Chen, Jianfeng Gao, Tuo Zhao
  
  Empirical Methods in Natural Language Processing | March 2021
  
  Publication
- GLGE: A New General Language Generation Evaluation Benchmark
  
  Dayiheng Liu, Yu Yan, Yeyun Gong, Weizhen Qi, Hang Zhang, Jian Jiao, Wei Chen, Jie Fu, Linjun Shou, Ming Gong (YIMING), Pengcheng Wang, Jiusheng Chen, Daxin Jiang (姜大昕), Jiancheng Lv, Ruofei Zhang, Winnie Wu, Ming Zhou, Nan Duan
  
  ACL-IJCNLP 2021 | November 2020
  
  Publication Access
- Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting
  
  Yue Wang, Wei Chen, Yuting Liu, Zhi-Ming Ma, Tie-Yan Liu
  
  Advances in Neural Information Processing Systems | December 2017
  
  Publication

- Embedding-Space Orthogonal Decomposition for Robust Social Recommendation
  
  Rongfeng Guo, Yinxuan Huang, Wei Chen, Mingyang Zhou, Yusen Wu, Yangchen Zeng, Han Chen, Hao Liao
  
  2026 the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) | August 2026
  
  PDF
- PaT: Planning-after-Trial for Efficient Test-Time Code Generation
  
  Youngsik Yoon, Sungjae Lee, Seockbean Song, Siwei Wang, Wei Chen, Jungseul Ok
  
  The 64th Annual Meeting of the Association for Computational Linguistics (ACL), Main Conference | July 2026
  
  PDF
- Toward Consistent World Models with Multi-Token Prediction and Latent Semantic Enhancement
  
  Qimin Zhong, Hao Liao, Haiming Qin, Mingyang Zhou, Rui Mao, Wei Chen, Naipeng Chao
  
  The 64th Annual Meeting of the Association for Computational Linguistics (ACL), Main Conference | July 2026
  
  Publication
- Semantic Caching for Low-Cost LLM Serving: From Offline Learning to Online Adaptation
  
  Xutong Liu, Baran Atalar, Xiangxiang Dai, Jinhang Zuo, Siwei Wang, John C.S. Lui, Wei Chen, Carlee Joe-Wong
  
  IEEE International Conference on Computer Communications (INFOCOM) | May 2026
  
  PDF Preprint
- Latent-DARM: Bridging Discrete Diffusion and Autoregressive Models for Reasoning
  
  Lina Berrayana, Ahmed Heakl, Muhammad Abdullah Sohail, Thomas Hofmann, Salman Khan, Wei Chen
  
  Proceedings of Workshop on Latent & Implicit Thinking – Going Beyond CoT Reasoning (LIT), the 14th International Conference on Learning Representations (ICLR) | April 2026
  
  PDF Preprint
- Combinatorial Rising Bandits
  
  Seockbean Song, Youngsik Yoon, Siwei Wang, Wei Chen, Jungseul Ok
  
  The 14th International Conference on Learning Representations (ICLR) | April 2026
  
  PDF Preprint
- Benefits and Pitfalls of Reinforcement Learning for Language Model Planning: A Theoretical Perspective
  
  Siwei Wang, Yifei Shen, Haoran Sun, Shi Feng, Shang-Hua Teng, Li Dong, Yaru Hao, Wei Chen
  
  The 14th International Conference on Learning Representations (ICLR) | April 2026
  
  PDF DOI Publication
- Mechanism Design for LLM Fine-tuning with Multiple Reward Models
  
  Haoran Sun, Yurong Chen, Siwei Wang, Xu Chu, Wei Chen, Xiaotie Deng
  
  Neural Information Processing Systems (NeurIPS) 2025 | December 2025
  
  PDF
- Offline Learning for Combinatorial Multi-armed Bandits
  
  Xutong Liu, Xiangxiang Dai, Jinhang Zuo, Siwei Wang, Carlee Joe-Wong, John C.S. Lui, Wei Chen
  
  Proceedings of the 42nd International Conference on Machine Learning (ICML) | July 2025
  
  PDF
- Structural-Entropy-Based Sample Selection for Efficient and Effective Learning
  
  Tianchi Xie, Jiangning Zhu, Guozu Ma, Minzhi Lin, Wei Chen, Weikai Yang, Shixia Liu
  
  Proceedings of the 13th International Conference on Learning Representations (ICLR) | April 2025
  
  PDF
- Convergence to Equilibrium of No-regret Dynamics in Congestion Games
  
  Volkan Cevher, Wei Chen, Leello Dadi, Jing Dong, Ioannis Panageas, Stratis Skoulakis, Luca Viano, Baoxiang Wang, Siwei Wang, Jingyu Wu
  
  Conference on Web and Internet Economics (WINE) | December 2024
  
  PDF Publication
- Combinatorial Causal Bandits without Graph Skeleton
  
  Shi Feng, Nuoya Xiong, Wei Chen
  
  Proceedings of the 16th Asian Conference on Machine Learning (ACML) | December 2024
  
  PDF
- Query-Efficient Correlation Clustering with Noisy Oracle
  
  Yuko Kuroki, Atsushi Miyauchi, Francesco Bonchi, Wei Chen
  
  NeurIPS 2024 | December 2024
  
  PDF DOI
- Combinatorial Multivariant Multi-Armed Bandits with Applications to Episodic Reinforcement Learning and Beyond
  
  Xutong Liu, Siwei Wang, Jinhang Zuo, Han Zhong, Xuchuang Wang, Zhiyong Wang, Shuai Li, Mohammad Hajiesmaili, John C.S. Lui, Wei Chen
  
  Proceedings of the 41st International Conference on Machine Learning (ICML) | July 2024
  
  PDF
- Combinatorial Bandits for Maximum Value Reward Function under Value-index Feedback
  
  Yiliu Wang, Wei Chen, Milan Vojnovic
  
  Proceedings of the 12th International Conference on Learning Representations (ICLR) | May 2024
  
  PDF
- Cascading Reinforcement Learning
  
  Yihan Du, R. Srikant, Wei Chen
  
  Proceedings of the 12th International Conference on Learning Representations (ICLR) | May 2024
  
  PDF
- Scalable Fair Influence Maximization
  
  Xiaobin Rui, Zhixiao Wang, Jiayu Zhao, Lichao Sun, Wei Chen
  
  Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS) | December 2023
  
  PDF Preprint
- Mitigating Filter Bubbles Under a Competitive Diffusion Model
  
  Prithu Banerjee, Wei Chen, Laks V.S. Lakshmanan
  
  Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD) | June 2023
  
  PDF
- Popularity Ratio Maximization: Surpassing Competitors through Influence Propagation
  
  Hao Liao, Sheng Bi, Jiao Wu, Wei Zhang, Mingyang Zhou, Rui Mao, Wei Chen
  
  Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD) | June 2023
  
  PDF
- Collaborative Pure Exploration in Kernel Bandit
  
  Yihan Du, Wei Chen, Yuko Kuroki, Longbo Huang
  
  Proceedings of the 11th International Conference on Learning Representations (ICLR) | May 2023
  
  PDF
- Combinatorial Pure Exploration of Causal Bandits
  
  Nuoya Xiong, Wei Chen
  
  Proceedings of the 11th International Conference on Learning Representations (ICLR) | May 2023
  
  PDF
- Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
  
  Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan (Jana) Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian
  
  International Conference on Learning Representations (ICLR) 2023 | May 2023
  
  Publication Project
- Denoising Masked Auto-encoders Helps Robust Classification
  
  QuanLin Wu, Hang Ye, Yuntian Gu, Huishuai Zhang, Liwei Wang, Di He
  
  International Conference on Learning Representations (ICLR) 2023 | May 2023
  
  Publication
- Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks
  
  Huishuai Zhang, Da Yu, Yiping Lu, Di He
  
  International Conference on Artificial Intelligence and Statistics (AIStats) | April 2023
  
  Preprint
- Combinatorial Causal Bandits
  
  Shi Feng, Wei Chen
  
  Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI) | February 2023
  
  PDF Preprint
- Scalable Adversarial Attack Algorithms on Influence Maximization
  
  Lichao Sun, Xiaobin Rui, Wei Chen
  
  Proceedings of the 16th ACM International WSDM Conference (WSDM) | February 2023
  
  PDF Preprint
- Does Momentum Change the Implicit Regularization on Separable Data?
  
  Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
  
  NeurIPS 2022 | November 2022
  
  Publication
- Batch-Size Independent Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms or Independent Arms
  
  Xutong Liu, Jinhang Zuo, Siwei Wang, Carlee Joe-Wong, John C.S. Lui, Wei Chen
  
  Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS) | November 2022
  
  PDF
- Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret
  
  Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu
  
  Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS) | November 2022
  
  PDF
- Availability attacks create shortcuts
  
  Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu, Jian Yin
  
  Knowledge Discovery and Data Mining | August 2022
  
  Publication
- Branching Reinforcement Learning
  
  Yihan Du, Wei Chen
  
  Proceedings of the 39th International Conference on Machine Learning (ICML) | July 2022
  
  PDF Preprint
- Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum
  
  Zeke Xie, Xinrui Wang, Huishuai Zhang, Issei Sato, Masashi Sugiyama
  
  ICML 2022 | July 2022
  
  Publication
- PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior
  
  Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu
  
  ICLR 2022 | April 2022
  
  Publication
- Gradient Information Matters in Policy Optimization by Back-propagating through Model
  
  Chongchong Li, Yue Wang, Wei Chen, Yuting Liu, Zhi-Ming Ma, Tie-Yan Liu
  
  ICLR 2022 | April 2022
  
  Publication
- Differentially private fine-tuning of language models
  
  Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Gautam Kamath, Janardhan (Jana) Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang
  
  ICLR 2022 | April 2022
  
  Publication Project
- Online Competitive Influence Maximization
  
  Jinhang Zuo, Xutong Liu, Carlee Joe-Wong, John C.S. Lui, Wei Chen
  
  Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS) | March 2022
  
  PDF
- Online Influence Maximization under the Independent Cascade Model with Node-Level Feedback
  
  Zhijie Zhang, Wei Chen, Xiaoming Sun, Jialin Zhang
  
  Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI) | February 2022
  
  This version fixed some bugs contained in the published version. See footnote in the first page.
  
  PDF
- Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD
  
  Bohan Wang, Huishuai Zhang, Jieyu Zhang, Qi Meng, Wei Chen, Tie-Yan Liu
  
  NeurIPS 2021 | December 2021
  
  Publication
- Learning Causal Semantic Representation for Out-of-Distribution Prediction
  
  Chang Liu, Xinwei Sun, Jindong Wang, Haoyue Tang, Tao Li, Tao Qin, Wei Chen, Tie-Yan Liu
  
  NeurIPS 2021 | December 2021
  
  Publication
- Recovering Latent Causal Factor for Generalization to Distributional Shifts
  
  Xinwei Sun, Botong Wu, Xiangyu Zheng, Chang Liu, Wei Chen, Tao Qin, Tie-Yan Liu
  
  NeurIPS 2021 | December 2021
  
  Publication
- R-Drop: Regularized Dropout for Neural Networks
  
  xiaobo liang, Lijun Wu, Juntao Li, Yue Wang, Qi Meng, Tao Qin, Wei Chen, Min Zhang, Tie-Yan Liu
  
  NeurIPS 2021 | December 2021
  
  Publication
- Combinatorial Pure Exploration with Bottleneck Reward Function
  
  Yihan Du, Yuko Kuroki, Wei Chen
  
  Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS) | December 2021
  
  PDF Publication
- The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle
  
  Fang Kong, Yueran Yang, Wei Chen, Shuai Li
  
  Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS) | December 2021
  
  PDF Publication
- Causal Inference for Influence Propagation — Identifiability of the Independent Cascade Model
  
  Shi Feng, Wei Chen
  
  Proceedings of the 10th International Conference on Computational Social Networks (CSoNet’2021) | November 2021
  
  Winner of the sole Best Paper Award
  
  PDF
- Contextual Bandit Applications in a Customer Support Bot
  
  Sandra Sajeev, Jade Huang, Nikos Karampatziakis, Sebastian Kochman, Matthew Hall, Wei Chen
  
  KDD 2021 | August 2021
  
  Publication Publication
- Maximizing Social Welfare in a Competitive Diffusion Model
  
  Prithu Banerjee, Wei Chen, Laks V.S. Lakshmanan
  
  VLDB 2021 | August 2021
  
  PDF Publication
- Poolingformer: Long Document Modeling with Pooling Attention
  
  Hang Zhang, Yeyun Gong, Yelong Shen, Weisheng Li, Jiancheng Lv, Nan Duan, Wei Chen
  
  2021 International Conference on Machine Learning | July 2021
  
  Publication Publication
- The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks
  
  Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu
  
  2021 International Conference on Machine Learning | July 2021
  
  Publication
- Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning
  
  Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui
  
  2021 International Conference on Machine Learning (ICML) | July 2021
  
  PDF Publication
- Network Inference and Influence Maximization from Samples
  
  Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
  
  2021 International Conference on Machine Learning (ICML) | July 2021
  
  PDF Publication
- Large Scale Private Learning via Low-rank Reparametrization
  
  Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
  
  International Conference on Machine Learning (ICML) | July 2021
  
  PDF
- Combinatorial Semi-Bandit in the Non-Stationary Environment
  
  Wei Chen, Liwei Wang, Haoyu Zhao, Kai Zheng
  
  Conference on Uncertainty in Artificial Intelligence (UAI) 2021 | June 2021
  
  PDF Publication
- Memory-Efficient Differentiable Transformer Architecture Search
  
  Yuekai Zhao, Li Dong, Yelong Shen, Zhihua Zhang, Furu Wei, Wei Chen
  
  ACL-IJCNLP 2021 | May 2021
  
  Publication
- Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization
  
  Chen Liang, Simiao Zuo, Minshuo Chen, Haoming Jiang, Xiaodong Liu, Pengcheng He, Tuo Zhao, Wei Chen
  
  ACL-IJCNLP 2021 | May 2021
  
  Publication
- DeBERTa: Decoding-Enhanced BERT with Disentangled Attention
  
  Pengcheng He, Xiaodong Liu, Jianfeng Gao, Wei Chen
  
  2021 International Conference on Learning Representations | May 2021
  
  Under review
  
  PDF Publication Github Project Project
- Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning
  
  Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu
  
  ICLR 2021 | May 2021
  
  Publication
- Token-wise Curriculum Learning for Neural Machine Translation
  
  Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Wei Chen, Jianfeng Gao, Tuo Zhao
  
  Empirical Methods in Natural Language Processing | March 2021
  
  Publication
- Combinatorial Pure Exploration with Full-Bandit or Partial Linear Feedback
  
  Yihan Du, Yuko Kuroki, Wei Chen
  
  Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI) | February 2021
  
  PDF
- How Does Data Augmentation Affect Privacy in Machine Learning?
  
  Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
  
  AAAI 2021 | January 2021
  
  Publication
- BANG: Bridging Autoregressive and Non-autoregressive Generation with Large Scale Pretraining
  
  Weizhen Qi, Yeyun Gong, Jian Jiao, Yu Yan, Dayiheng Liu, Wei Chen, Kewen Tang, Houqiang Li, Jiusheng Chen, Ruofei Zhang, Ming Zhou, Nan Duan
  
  2021 International Conference on Machine Learning | December 2020
  
  Publication
- Online Influence Maximization under Linear Threshold Model
  
  Shuai Li, Fang Kong, Kejie Tang, Qizhi Li, Wei Chen
  
  Proceedings of the 33rd Conference on Neural Information Processing Systems (NeurIPS) | December 2020
  
  Some typos in the original NeurIPS'2020 paper have been fixed.
  
  PDF
- GLGE: A New General Language Generation Evaluation Benchmark
  
  Dayiheng Liu, Yu Yan, Yeyun Gong, Weizhen Qi, Hang Zhang, Jian Jiao, Wei Chen, Jie Fu, Linjun Shou, Ming Gong (YIMING), Pengcheng Wang, Jiusheng Chen, Daxin Jiang (姜大昕), Jiancheng Lv, Ruofei Zhang, Winnie Wu, Ming Zhou, Nan Duan
  
  ACL-IJCNLP 2021 | November 2020
  
  Publication Access
- Thompson Sampling for Combinatorial Semi-Bandits
  
  Siwei Wang, Wei Chen
  
  Proceedings of the 35th International Conference on Machine Learning (ICML’2018) | July 2018
  
  PDF
- Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting
  
  Yue Wang, Wei Chen, Yuting Liu, Zhi-Ming Ma, Tie-Yan Liu
  
  Advances in Neural Information Processing Systems | December 2017
  
  Publication
- Combinatorial Pure Exploration of Multi-Armed Bandits
  
  Shouyuan Chen, Tian Lin, Irwin King, Michael R. Lyu, Wei Chen
  
  Proceedings of the 28th Annual Conference on Advances in Neural Information Processing Systems (NIPS’2014) | December 2014
  
  The PDF download link contains some bug fixes to the original paper.
  
  PDF
- Influence Maximization in Social Networks When Negative Opinions May Emerge and Propagate
  
  Wei Chen, Alex Collins, Rachel Cummings, Te Ke, Zhenming Liu, David Rincon, Xiaorui Sun, Wei Wei, Yajun Wang, Yifei Yuan
  
  Proceedings of the 11th SIAM International Conference on Data Mining (SDM) | April 2011
  
  PDF Preprint
- A Scalable Algorithm for Fair Influence Maximization with Unbiased Estimator
  
  Xiaobin Rui, Zhixiao Wang, Hao Peng, Wei Chen, Philip S. Yu
  
  IEEE Transactions on Knowledge and Data Engineering (TKDE) | May 2025
  
  PDF
- Uncovering Milestone Papers: A Network Diffusion and Game Theory Approach
  
  Wei Zhang, Juyang Cao, Manuel Sebastian Mariani, Zhen-Zhen Wang, Mingyang Zhou, Wei Chen, Hao Liao
  
  Journal of Informetrics | August 2024, Vol 18(3)
  
  Publication
- Selective Pre-training for Private Fine-tuning
  
  Da Yu, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Zinan Lin, Saurabh Naik, Tomasz Lukasz Religa, Jian Yin, Huishuai Zhang
  
  TMLR | May 2024
  
  Publication Publication Project
- Stabilize Deep ResNet with A Sharp Scaling Factor τ
  
  Huishuai Zhang, Da Yu, Mingyang Yi, Wei Chen, Tie-Yan Liu
  
  Machine Learning | September 2022
  
  Publication Publication
- The pure exploration problem with general reward functions depending on full distributions
  
  Siwei Wang, Wei Chen
  
  Machine Learning | July 2022
  
  Publication
- Adaptive Greedy versus Non-Adaptive Greedy for Influence Maximization
  
  Wei Chen, Binghui Peng, Grant Schoenebeck, Biaoshuai Tao
  
  Journal of Artificial Intelligence Research | May 2022, Vol 74: pp. 303-351
  
  PDF
- Higher Order Monotonicity and Submodularity of Influence in Social Networks: From Local to Global
  
  Wei Chen, Qiang Li, Xiaohan Shan, Xiaoming Sun, Jialin Zhang
  
  Information and Computation | January 2022
  
  PDF
- 基于优化反馈的组合在线学习 (Combinatorial Online Learning Based on Optimizing feedbacks）
  
  Fang Kong, Yueran Yang, Wei Chen, Shuai Li
  
  大数据（Big Data Research） | September 2021, Vol 7(5)
  
  PDF
- 基于样本的优化（Optimization from Samples）
  
  Zhijie Zhang, Xiaoming Sun, Jialin Zhang, Wei Chen
  
  大数据（Big Data Research） | September 2021, Vol 7(5): pp. 100-110
  
  PDF
- Target Transfer Q-learning and Its Convergence Analysis
  
  Yue Wang, Yuting Liu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
  
  Neurocomputing | June 2020
- Path-BN: Towards Effective Batch Normalization in the Path Space for ReLU Networks
  
  Xufang Luo, Qi Meng, Wei Chen, Tie-Yan Liu
  
  June 2021

MSR Asia Theory Center

Publications

Embedding-Space Orthogonal Decomposition for Robust Social Recommendation

PaT: Planning-after-Trial for Efficient Test-Time Code Generation

Toward Consistent World Models with Multi-Token Prediction and Latent Semantic Enhancement

Semantic Caching for Low-Cost LLM Serving: From Offline Learning to Online Adaptation

Benefits and Pitfalls of Reinforcement Learning for Language Model Planning: A Theoretical Perspective

Combinatorial Rising Bandits

Latent-DARM: Bridging Discrete Diffusion and Autoregressive Models for Reasoning

Mechanism Design for LLM Fine-tuning with Multiple Reward Models

Offline Learning for Combinatorial Multi-armed Bandits

A Scalable Algorithm for Fair Influence Maximization with Unbiased Estimator

Structural-Entropy-Based Sample Selection for Efficient and Effective Learning

Combinatorial Causal Bandits without Graph Skeleton

Convergence to Equilibrium of No-regret Dynamics in Congestion Games

Query-Efficient Correlation Clustering with Noisy Oracle

Uncovering Milestone Papers: A Network Diffusion and Game Theory Approach

Combinatorial Multivariant Multi-Armed Bandits with Applications to Episodic Reinforcement Learning and Beyond

Cascading Reinforcement Learning

Combinatorial Bandits for Maximum Value Reward Function under Value-index Feedback

Selective Pre-training for Private Fine-tuning

Scalable Fair Influence Maximization

Mitigating Filter Bubbles Under a Competitive Diffusion Model

Popularity Ratio Maximization: Surpassing Competitors through Influence Propagation

Collaborative Pure Exploration in Kernel Bandit

Combinatorial Pure Exploration of Causal Bandits

Denoising Masked Auto-encoders Helps Robust Classification

Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping

Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks

Combinatorial Causal Bandits

Scalable Adversarial Attack Algorithms on Influence Maximization

Does Momentum Change the Implicit Regularization on Separable Data?

Batch-Size Independent Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms or Independent Arms

Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret

Stabilize Deep ResNet with A Sharp Scaling Factor τ

Availability attacks create shortcuts

The pure exploration problem with general reward functions depending on full distributions

Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum

Branching Reinforcement Learning

Adaptive Greedy versus Non-Adaptive Greedy for Influence Maximization

Differentially private fine-tuning of language models

Gradient Information Matters in Policy Optimization by Back-propagating through Model

PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior

Online Competitive Influence Maximization

Online Influence Maximization under the Independent Cascade Model with Node-Level Feedback

Higher Order Monotonicity and Submodularity of Influence in Social Networks: From Local to Global

Combinatorial Pure Exploration with Bottleneck Reward Function

Learning Causal Semantic Representation for Out-of-Distribution Prediction

Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD

R-Drop: Regularized Dropout for Neural Networks

Recovering Latent Causal Factor for Generalization to Distributional Shifts

The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle

Causal Inference for Influence Propagation — Identifiability of the Independent Cascade Model

基于优化反馈的组合在线学习 (Combinatorial Online Learning Based on Optimizing feedbacks）

基于样本的优化（Optimization from Samples）

Contextual Bandit Applications in a Customer Support Bot

Maximizing Social Welfare in a Competitive Diffusion Model

Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning

Poolingformer: Long Document Modeling with Pooling Attention

The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks

Large Scale Private Learning via Low-rank Reparametrization

Network Inference and Influence Maximization from Samples

Combinatorial Semi-Bandit in the Non-Stationary Environment

Path-BN: Towards Effective Batch Normalization in the Path Space for ReLU Networks

Memory-Efficient Differentiable Transformer Architecture Search

Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization

DeBERTa: Decoding-Enhanced BERT with Disentangled Attention

Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning

Token-wise Curriculum Learning for Neural Machine Translation

Combinatorial Pure Exploration with Full-Bandit or Partial Linear Feedback

How Does Data Augmentation Affect Privacy in Machine Learning?

BANG: Bridging Autoregressive and Non-autoregressive Generation with Large Scale Pretraining

Online Influence Maximization under Linear Threshold Model

GLGE: A New General Language Generation Evaluation Benchmark

Target Transfer Q-learning and Its Convergence Analysis

Thompson Sampling for Combinatorial Semi-Bandits

Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting

Combinatorial Pure Exploration of Multi-Armed Bandits

Influence Maximization in Social Networks When Negative Opinions May Emerge and Propagate

Embedding-Space Orthogonal Decomposition for Robust Social Recommendation