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
Papiers de Collaboration
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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
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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
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Combinatorial Causal Bandits without Graph Skeleton
Shi Feng, Nuoya Xiong, Wei Chen
Proceedings of the 16th Asian Conference on Machine Learning (ACML) | December 2024
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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
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Mechanism Design for LLM Fine-tuning with Multiple Reward Models
Haoran Sun, Yurong Chen, Siwei Wang, Wei Chen, Xiaotie Deng
Pluralistic Alignment Workshop in Neural Information Processing Systems (NeurIPS) | December 2024
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Query-Efficient Correlation Clustering with Noisy Oracle
Yuko Kuroki, Atsushi Miyauchi, Francesco Bonchi, Wei Chen
NeurIPS 2024 | December 2024
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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)
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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
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Cascading Reinforcement Learning
Yihan Du, R. Srikant, Wei Chen
Proceedings of the 12th International Conference on Learning Representations (ICLR) | May 2024
-
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
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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
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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
-
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
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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
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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
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Combinatorial Pure Exploration of Causal Bandits
Nuoya Xiong, Wei Chen
Proceedings of the 11th International Conference on Learning Representations (ICLR) | May 2023
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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
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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
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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
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Combinatorial Causal Bandits
Shi Feng, Wei Chen
Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI) | February 2023
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Scalable Adversarial Attack Algorithms on Influence Maximization
Lichao Sun, Xiaobin Rui, Wei Chen
Proceedings of the 16th ACM International WSDM Conference (WSDM) | February 2023
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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
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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
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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
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Stabilize Deep ResNet with A Sharp Scaling Factor τ
Huishuai Zhang, Da Yu, Mingyang Yi, Wei Chen, Tie-Yan Liu
Machine Learning | September 2022
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Availability attacks create shortcuts
Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu, Jian Yin
2022 Knowledge Discovery and Data Mining | August 2022
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The pure exploration problem with general reward functions depending on full distributions
Machine Learning | July 2022
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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
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Branching Reinforcement Learning
Yihan Du, Wei Chen
Proceedings of the 39th International Conference on Machine Learning (ICML) | July 2022
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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
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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
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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
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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
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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
-
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.
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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
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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
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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
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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
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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
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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
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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
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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
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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)
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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
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Contextual Bandit Applications in a Customer Support Bot
Sandra Sajeev, Jade Huang, Nikos Karampatziakis, Sebastian Kochman, Matthew Hall, Wei Chen
KDD 2021 | August 2021
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Maximizing Social Welfare in a Competitive Diffusion Model
Prithu Banerjee, Wei Chen, Laks V.S. Lakshmanan
VLDB 2021 | August 2021
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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
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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
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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
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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
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Network Inference and Influence Maximization from Samples
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
2021 International Conference on Machine Learning (ICML) | July 2021
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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
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Path-BN: Towards Effective Batch Normalization in the Path Space for ReLU Networks
Xufang Luo, Qi Meng, Wei Chen, Tie-Yan Liu
June 2021
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Memory-Efficient Differentiable Transformer Architecture Search
Yuekai Zhao, Li Dong, Yelong Shen, Zhihua Zhang, Furu Wei, Wei Chen
ACL-IJCNLP 2021 | May 2021
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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
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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
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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
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Token-wise Curriculum Learning for Neural Machine Translation
Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Wei Chen, Jianfeng Gao, Tuo Zhao
2021 Empirical Methods in Natural Language Processing | March 2021
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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
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How Does Data Augmentation Affect Privacy in Machine Learning?
Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
AAAI 2021 | January 2021
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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
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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
Some typos in the original NeurIPS'2020 paper have been fixed.
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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
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Target Transfer Q-learning and Its Convergence Analysis
Yue Wang, Yuting Liu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
Neurocomputing | June 2020
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Thompson Sampling for Combinatorial Semi-Bandits
Proceedings of the 35th International Conference on Machine Learning (ICML’2018) | July 2018
-
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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
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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.
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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
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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
-
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
-
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
-
Mechanism Design for LLM Fine-tuning with Multiple Reward Models
Haoran Sun, Yurong Chen, Siwei Wang, Wei Chen, Xiaotie Deng
Pluralistic Alignment Workshop in Neural Information Processing Systems (NeurIPS) | December 2024
-
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
-
Combinatorial Causal Bandits without Graph Skeleton
Shi Feng, Nuoya Xiong, Wei Chen
Proceedings of the 16th Asian Conference on Machine Learning (ACML) | December 2024
-
Query-Efficient Correlation Clustering with Noisy Oracle
Yuko Kuroki, Atsushi Miyauchi, Francesco Bonchi, Wei Chen
NeurIPS 2024 | December 2024
-
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)
-
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
-
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
-
Cascading Reinforcement Learning
Yihan Du, R. Srikant, Wei Chen
Proceedings of the 12th International Conference on Learning Representations (ICLR) | May 2024
-
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
-
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
-
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
-
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
-
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
-
Combinatorial Pure Exploration of Causal Bandits
Nuoya Xiong, Wei Chen
Proceedings of the 11th International Conference on Learning Representations (ICLR) | May 2023
-
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
-
Combinatorial Causal Bandits
Shi Feng, Wei Chen
Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI) | February 2023
-
Scalable Adversarial Attack Algorithms on Influence Maximization
Lichao Sun, Xiaobin Rui, Wei Chen
Proceedings of the 16th ACM International WSDM Conference (WSDM) | February 2023
-
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
-
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
-
Availability attacks create shortcuts
Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu, Jian Yin
2022 Knowledge Discovery and Data Mining | August 2022
-
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
-
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
-
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
-
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
-
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.
-
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
-
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
-
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
-
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
-
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)
-
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
-
Maximizing Social Welfare in a Competitive Diffusion Model
Prithu Banerjee, Wei Chen, Laks V.S. Lakshmanan
VLDB 2021 | August 2021
-
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
-
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
-
Network Inference and Influence Maximization from Samples
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
2021 International Conference on Machine Learning (ICML) | July 2021
-
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
-
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
-
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
-
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.
-
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
Proceedings of the 35th International Conference on Machine Learning (ICML’2018) | July 2018
-
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
-
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.
-
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
-
-
-
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
-
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
-
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
-
Mechanism Design for LLM Fine-tuning with Multiple Reward Models
Haoran Sun, Yurong Chen, Siwei Wang, Wei Chen, Xiaotie Deng
Pluralistic Alignment Workshop in Neural Information Processing Systems (NeurIPS) | December 2024
-
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
-
Combinatorial Causal Bandits without Graph Skeleton
Shi Feng, Nuoya Xiong, Wei Chen
Proceedings of the 16th Asian Conference on Machine Learning (ACML) | December 2024
-
Query-Efficient Correlation Clustering with Noisy Oracle
Yuko Kuroki, Atsushi Miyauchi, Francesco Bonchi, Wei Chen
NeurIPS 2024 | December 2024
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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
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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
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Cascading Reinforcement Learning
Yihan Du, R. Srikant, Wei Chen
Proceedings of the 12th International Conference on Learning Representations (ICLR) | May 2024
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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
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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
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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
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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
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Combinatorial Pure Exploration of Causal Bandits
Nuoya Xiong, Wei Chen
Proceedings of the 11th International Conference on Learning Representations (ICLR) | May 2023
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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
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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
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Combinatorial Causal Bandits
Shi Feng, Wei Chen
Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI) | February 2023
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Scalable Adversarial Attack Algorithms on Influence Maximization
Lichao Sun, Xiaobin Rui, Wei Chen
Proceedings of the 16th ACM International WSDM Conference (WSDM) | February 2023
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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
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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
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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
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Stabilize Deep ResNet with A Sharp Scaling Factor τ
Huishuai Zhang, Da Yu, Mingyang Yi, Wei Chen, Tie-Yan Liu
Machine Learning | September 2022
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The pure exploration problem with general reward functions depending on full distributions
Machine Learning | July 2022
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Branching Reinforcement Learning
Yihan Du, Wei Chen
Proceedings of the 39th International Conference on Machine Learning (ICML) | July 2022
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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
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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
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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
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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
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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
This version fixed some bugs contained in the published version. See footnote in the first page.
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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
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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
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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
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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
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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
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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
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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
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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
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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)
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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
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Contextual Bandit Applications in a Customer Support Bot
Sandra Sajeev, Jade Huang, Nikos Karampatziakis, Sebastian Kochman, Matthew Hall, Wei Chen
KDD 2021 | August 2021
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Maximizing Social Welfare in a Competitive Diffusion Model
Prithu Banerjee, Wei Chen, Laks V.S. Lakshmanan
VLDB 2021 | August 2021
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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
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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
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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
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Network Inference and Influence Maximization from Samples
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
2021 International Conference on Machine Learning (ICML) | July 2021
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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
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Path-BN: Towards Effective Batch Normalization in the Path Space for ReLU Networks
Xufang Luo, Qi Meng, Wei Chen, Tie-Yan Liu
June 2021
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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
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Memory-Efficient Differentiable Transformer Architecture Search
Yuekai Zhao, Li Dong, Yelong Shen, Zhihua Zhang, Furu Wei, Wei Chen
ACL-IJCNLP 2021 | May 2021
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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
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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
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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
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How Does Data Augmentation Affect Privacy in Machine Learning?
Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
AAAI 2021 | January 2021
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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
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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
Some typos in the original NeurIPS'2020 paper have been fixed.
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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
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Target Transfer Q-learning and Its Convergence Analysis
Yue Wang, Yuting Liu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
Neurocomputing | June 2020
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Thompson Sampling for Combinatorial Semi-Bandits
Proceedings of the 35th International Conference on Machine Learning (ICML’2018) | July 2018
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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
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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.
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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
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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
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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
-
Scalable Adversarial Attack Algorithms on Influence Maximization
Lichao Sun, Xiaobin Rui, Wei Chen
Proceedings of the 16th ACM International WSDM Conference (WSDM) | February 2023
-
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
-
Maximizing Social Welfare in a Competitive Diffusion Model
Prithu Banerjee, Wei Chen, Laks V.S. Lakshmanan
VLDB 2021 | August 2021
-
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.
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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
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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)
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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
-
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
-
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.
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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
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Network Inference and Influence Maximization from Samples
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
2021 International Conference on Machine Learning (ICML) | July 2021
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Mechanism Design for LLM Fine-tuning with Multiple Reward Models
Haoran Sun, Yurong Chen, Siwei Wang, Wei Chen, Xiaotie Deng
Pluralistic Alignment Workshop in Neural Information Processing Systems (NeurIPS) | December 2024
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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
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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
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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
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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
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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
-
Availability attacks create shortcuts
Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu, Jian Yin
2022 Knowledge Discovery and Data Mining | August 2022
-
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
-
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
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How Does Data Augmentation Affect Privacy in Machine Learning?
Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
AAAI 2021 | January 2021
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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
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Token-wise Curriculum Learning for Neural Machine Translation
Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Wei Chen, Jianfeng Gao, Tuo Zhao
2021 Empirical Methods in Natural Language Processing | March 2021
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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
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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
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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
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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
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Mechanism Design for LLM Fine-tuning with Multiple Reward Models
Haoran Sun, Yurong Chen, Siwei Wang, Wei Chen, Xiaotie Deng
Pluralistic Alignment Workshop in Neural Information Processing Systems (NeurIPS) | December 2024
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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
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Combinatorial Causal Bandits without Graph Skeleton
Shi Feng, Nuoya Xiong, Wei Chen
Proceedings of the 16th Asian Conference on Machine Learning (ACML) | December 2024
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Query-Efficient Correlation Clustering with Noisy Oracle
Yuko Kuroki, Atsushi Miyauchi, Francesco Bonchi, Wei Chen
NeurIPS 2024 | December 2024
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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
-
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
-
Cascading Reinforcement Learning
Yihan Du, R. Srikant, Wei Chen
Proceedings of the 12th International Conference on Learning Representations (ICLR) | May 2024
-
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
-
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
-
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
-
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
-
Combinatorial Pure Exploration of Causal Bandits
Nuoya Xiong, Wei Chen
Proceedings of the 11th International Conference on Learning Representations (ICLR) | May 2023
-
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
-
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
-
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
-
Combinatorial Causal Bandits
Shi Feng, Wei Chen
Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI) | February 2023
-
Scalable Adversarial Attack Algorithms on Influence Maximization
Lichao Sun, Xiaobin Rui, Wei Chen
Proceedings of the 16th ACM International WSDM Conference (WSDM) | February 2023
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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
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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
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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
-
Availability attacks create shortcuts
Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu, Jian Yin
2022 Knowledge Discovery and Data Mining | August 2022
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Branching Reinforcement Learning
Yihan Du, Wei Chen
Proceedings of the 39th International Conference on Machine Learning (ICML) | July 2022
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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
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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
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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
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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
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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
-
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.
-
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
-
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
-
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
-
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
-
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
-
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
-
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
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Contextual Bandit Applications in a Customer Support Bot
Sandra Sajeev, Jade Huang, Nikos Karampatziakis, Sebastian Kochman, Matthew Hall, Wei Chen
KDD 2021 | August 2021
-
Maximizing Social Welfare in a Competitive Diffusion Model
Prithu Banerjee, Wei Chen, Laks V.S. Lakshmanan
VLDB 2021 | August 2021
-
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
-
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
-
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
-
Network Inference and Influence Maximization from Samples
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
2021 International Conference on Machine Learning (ICML) | July 2021
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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
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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
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Memory-Efficient Differentiable Transformer Architecture Search
Yuekai Zhao, Li Dong, Yelong Shen, Zhihua Zhang, Furu Wei, Wei Chen
ACL-IJCNLP 2021 | May 2021
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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
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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
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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
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Token-wise Curriculum Learning for Neural Machine Translation
Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Wei Chen, Jianfeng Gao, Tuo Zhao
2021 Empirical Methods in Natural Language Processing | March 2021
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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
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How Does Data Augmentation Affect Privacy in Machine Learning?
Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
AAAI 2021 | January 2021
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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
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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
Some typos in the original NeurIPS'2020 paper have been fixed.
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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
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Thompson Sampling for Combinatorial Semi-Bandits
Proceedings of the 35th International Conference on Machine Learning (ICML’2018) | July 2018
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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
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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.
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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
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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
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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)
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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
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Stabilize Deep ResNet with A Sharp Scaling Factor τ
Huishuai Zhang, Da Yu, Mingyang Yi, Wei Chen, Tie-Yan Liu
Machine Learning | September 2022
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The pure exploration problem with general reward functions depending on full distributions
Machine Learning | July 2022
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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
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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
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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)
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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
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Target Transfer Q-learning and Its Convergence Analysis
Yue Wang, Yuting Liu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
Neurocomputing | June 2020
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Path-BN: Towards Effective Batch Normalization in the Path Space for ReLU Networks
Xufang Luo, Qi Meng, Wei Chen, Tie-Yan Liu
June 2021
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