Wei Chen

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 120

Top Venues

Publications

Bohan Wang, Yushun Zhang, Huishuai Zhang, Qi Meng, Ruoyu Sun, Zhi-Ming Ma, Tie-Yan Liu, Zhi-Quan Luo, Wei Chen
Provable Adaptivity of Adam under Non-uniform Smoothness. KDD (2024)
Yubao Tang, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Xueqi Cheng
Listwise Generative Retrieval Models via a Sequential Learning Process. CoRR (2024)
Yubao Tang, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Xueqi Cheng
Listwise Generative Retrieval Models via a Sequential Learning Process. ACM Trans. Inf. Syst. 42 (5) (2024)
Yu-An Liu, Ruqing Zhang, Mingkun Zhang, Wei Chen, Maarten de Rijke, Jiafeng Guo, Xueqi Cheng
Perturbation-Invariant Adversarial Training for Neural Ranking Models: Improving the Effectiveness-Robustness Trade-Off. AAAI (2024)
Bohan Wang, Huishuai Zhang, Qi Meng, Ruoyu Sun, Zhi-Ming Ma, Wei Chen
On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond. CoRR (2024)
Yixin Ji, Yang Xiang, Juntao Li, Wei Chen, Zhongyi Liu, Kehai Chen, Min Zhang
Feature-based Low-Rank Compression of Large Language Models via Bayesian Optimization. CoRR (2024)
Yuchen Wen, Keping Bi, Wei Chen, Jiafeng Guo, Xueqi Cheng
Evaluating Implicit Bias in Large Language Models by Attacking From a Psychometric Perspective. CoRR (2024)
Bohan Wang, Huishuai Zhang, Zhiming Ma, Wei Chen
Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions. COLT (2023)
Jiangui Chen, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Yixing Fan, Xueqi Cheng
Continual Learning for Generative Retrieval over Dynamic Corpora. CIKM (2023)
Yu-An Liu, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Yixing Fan, Xueqi Cheng
Black-box Adversarial Attacks against Dense Retrieval Models: A Multi-view Contrastive Learning Method. CIKM (2023)
Bohan Wang, Huishuai Zhang, Zhi-Ming Ma, Wei Chen
Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions. CoRR (2023)
Bohan Wang, Jingwen Fu, Huishuai Zhang, Nanning Zheng, Wei Chen
Closing the gap between the upper bound and lower bound of Adam's iteration complexity. NeurIPS (2023)
Yu-An Liu, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Yixing Fan, Xueqi Cheng
Black-box Adversarial Attacks against Dense Retrieval Models: A Multi-view Contrastive Learning Method. CoRR (2023)
Yu-An Liu, Ruqing Zhang, Jiafeng Guo, Wei Chen, Xueqi Cheng
On the Robustness of Generative Retrieval Models: An Out-of-Distribution Perspective. CoRR (2023)
Yu-An Liu, Ruqing Zhang, Mingkun Zhang, Wei Chen, Maarten de Rijke, Jiafeng Guo, Xueqi Cheng
Perturbation-Invariant Adversarial Training for Neural Ranking Models: Improving the Effectiveness-Robustness Trade-Off. CoRR (2023)
Bohan Wang, Jingwen Fu, Huishuai Zhang, Nanning Zheng, Wei Chen
Closing the Gap Between the Upper Bound and the Lower Bound of Adam's Iteration Complexity. CoRR (2023)
Wei Chen, Weitao Du, Zhi-Ming Ma, Qi Meng
Power-law Dynamic arising from machine learning. CoRR (2023)
Yihan Du, Wei Chen, Yuko Kuroki, Longbo Huang
Collaborative Pure Exploration in Kernel Bandit. ICLR (2023)
Jiangui Chen, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Yixing Fan, Xueqi Cheng
Continual Learning for Generative Retrieval over Dynamic Corpora. CoRR (2023)
Yu-An Liu, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Yixing Fan, Xueqi Cheng
Topic-oriented Adversarial Attacks against Black-box Neural Ranking Models. SIGIR (2023)
Jingwen Fu, Bohan Wang, Huishuai Zhang, Zhizheng Zhang, Wei Chen, Nanning Zheng
When and Why Momentum Accelerates SGD: An Empirical Study. CoRR (2023)
Xiaodong Yang, Huishuai Zhang, Wei Chen, Tie-Yan Liu
Normalized/Clipped SGD with Perturbation for Differentially Private Non-Convex Optimization. CoRR (2022)
Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu
Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret. CoRR (2022)
Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu
Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart. CVPR (2022)
Peiyan Hu, Qi Meng, Bingguang Chen, Shiqi Gong, Yue Wang, Wei Chen, Rongchan Zhu, Zhi-Ming Ma, Tie-Yan Liu
Neural Operator with Regularity Structure for Modeling Dynamics Driven by SPDEs. CoRR (2022)
Bohan Wang, Yushun Zhang, Huishuai Zhang, Qi Meng, Zhi-Ming Ma, Tie-Yan Liu, Wei Chen
Provable Adaptivity in Adam. CoRR (2022)
Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu
Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret. NeurIPS (2022)
Huishuai Zhang, Da Yu, Mingyang Yi, Wei Chen, Tie-Yan Liu
Stabilize deep ResNet with a sharp scaling factor τ. Mach. Learn. 111 (9) (2022)
Juanping Zhu, Qi Meng, Wei Chen, Yue Wang, Zhiming Ma
Constructing the Basis Path Set by Eliminating the Path Dependency. J. Syst. Sci. Complex. 35 (5) (2022)
Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
Does Momentum Change the Implicit Regularization on Separable Data? NeurIPS (2022)
Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu
PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior. ICLR (2022)
Yihan Du, Wei Chen
Branching Reinforcement Learning. CoRR (2022)
Yihan Du, Yuko Kuroki, Wei Chen
Combinatorial Pure Exploration with Full-Bandit or Partial Linear Feedback. AAAI (2021)
Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma
Momentum Doesn't Change the Implicit Bias. CoRR (2021)
Xinwei Sun, Botong Wu, Xiangyu Zheng, Chang Liu, Wei Chen, Tao Qin, Tie-Yan Liu
Recovering Latent Causal Factor for Generalization to Distributional Shifts. NeurIPS (2021)
Xiaobo Liang, Lijun Wu, Juntao Li, Yue Wang, Qi Meng, Tao Qin, Wei Chen, Min Zhang, Tie-Yan Liu
R-Drop: Regularized Dropout for Neural Networks. NeurIPS (2021)
Ziming Liu, Bohan Wang, Qi Meng, Wei Chen, Max Tegmark, Tie-Yan Liu
Machine-Learning Non-Conservative Dynamics for New-Physics Detection. CoRR (2021)
Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu
Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning. ICLR (2021)
Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
Indiscriminate Poisoning Attacks Are Shortcuts. CoRR (2021)
Mingyang Yi, Qi Meng, Wei Chen, Zhi-Ming Ma
Towards Accelerating Training of Batch Normalization: A Manifold Perspective. CoRR (2021)
Xiangyu Zheng, Xinwei Sun, Wei Chen, Tie-Yan Liu
Causally Invariant Predictor with Shift-Robustness. CoRR (2021)
Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui
Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning. CoRR (2021)
Juanping Zhu, Qi Meng, Wei Chen, Zhiming Ma
Interpreting the Basis Path Set in Neural Networks. J. Syst. Sci. Complex. 34 (6) (2021)
Chang Liu, Xinwei Sun, Jindong Wang, Haoyue Tang, Tao Li, Tao Qin, Wei Chen, Tie-Yan Liu
Learning Causal Semantic Representation for Out-of-Distribution Prediction. NeurIPS (2021)
Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui
Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning. ICML (2021)
Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu
Do Not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning. CoRR (2021)
Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu
PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Driven Adaptive Prior. CoRR (2021)
Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu
The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks. ICML (2021)
Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu
Adversarial Training with Rectified Rejection. CoRR (2021)
Bohan Wang, Huishuai Zhang, Jieyu Zhang, Qi Meng, Wei Chen, Tie-Yan Liu
Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD. NeurIPS (2021)
Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
How Does Data Augmentation Affect Privacy in Machine Learning? AAAI (2021)
Yihan Du, Yuko Kuroki, Wei Chen
Combinatorial Pure Exploration with Bottleneck Reward Function and its Extension to General Reward Functions. CoRR (2021)
Bohan Wang, Huishuai Zhang, Jieyu Zhang, Qi Meng, Wei Chen, Tie-Yan Liu
Optimizing Information-theoretical Generalization Bounds via Anisotropic Noise in SGLD. CoRR (2021)
Shiqi Gong, Qi Meng, Yue Wang, Lijun Wu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
Incorporating NODE with Pre-trained Neural Differential Operator for Learning Dynamics. CoRR (2021)
Yihan Du, Wei Chen, Yuko Kuroki, Longbo Huang
Collaborative Pure Exploration in Kernel Bandit. CoRR (2021)
Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
BN-invariant sharpness regularizes the training model to better generalization. CoRR (2021)
Xinwei Sun, Botong Wu, Wei Chen
Identifying Invariant Texture Violation for Robust Deepfake Detection. CoRR (2020)
Wei Chen, Yihan Du, Longbo Huang, Haoyu Zhao
Combinatorial Pure Exploration of Dueling Bandit. CoRR (2020)
Xufang Luo, Qi Meng, Di He, Wei Chen, Yunhong Wang
I4R: Promoting Deep Reinforcement Learning by the Indicator for Expressive Representations. IJCAI (2020)
Wei Chen, Yihan Du, Yuko Kuroki
Combinatorial Pure Exploration with Partial or Full-Bandit Linear Feedback. CoRR (2020)
Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
Membership Inference with Privately Augmented Data Endorses the Benign while Suppresses the Adversary. CoRR (2020)
Qi Meng, Shiqi Gong, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
Dynamic of Stochastic Gradient Descent with State-Dependent Noise. CoRR (2020)
Bohan Wang, Qi Meng, Wei Chen
The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks. CoRR (2020)
Xinwei Sun, Botong Wu, Chang Liu, Xiangyu Zheng, Wei Chen, Tao Qin, Tie-Yan Liu
Latent Causal Invariant Model. CoRR (2020)
Shicong Cen, Huishuai Zhang, Yuejie Chi, Wei Chen, Tie-Yan Liu
Convergence of Distributed Stochastic Variance Reduced Methods Without Sampling Extra Data. IEEE Trans. Signal Process. 68 (2020)
Jinhang Zuo, Xutong Liu, Carlee Joe-Wong, John C. S. Lui, Wei Chen
Online Competitive Influence Maximization. CoRR (2020)
Chang Liu, Xinwei Sun, Jindong Wang, Tao Li, Tao Qin, Wei Chen, Tie-Yan Liu
Learning Causal Semantic Representation for Out-of-Distribution Prediction. CoRR (2020)
Juanping Zhu, Qi Meng, Wei Chen, Yue Wang, Zhiming Ma
Constructing Basis Path Set by Eliminating Path Dependency. CoRR (2020)
Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
Gradient Perturbation is Underrated for Differentially Private Convex Optimization. IJCAI (2020)
Yue Wang, Yuting Liu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
Target transfer Q-learning and its convergence analysis. Neurocomputing 392 (2020)
Ling Pan, Qingpeng Cai, Qi Meng, Wei Chen, Longbo Huang
Reinforcement Learning with Dynamic Boltzmann Softmax Updates. IJCAI (2020)
Wei Chen, Yihan Du, Longbo Huang, Haoyu Zhao
Combinatorial Pure Exploration for Dueling Bandit. ICML (2020)
Juanping Zhu, Qi Meng, Wei Chen, Zhiming Ma
Interpreting Basis Path Set in Neural Networks. CoRR (2019)
Huishuai Zhang, Da Yu, Wei Chen, Tie-Yan Liu
Training Over-parameterized Deep ResNet Is almost as Easy as Training a Two-layer Network. CoRR (2019)
Li He, Shuxin Zheng, Wei Chen, Zhiming Ma, Tie-Yan Liu
OptQuant: Distributed training of neural networks with optimized quantization mechanisms. Neurocomputing 340 (2019)
Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu, Jian Yin
Gradient Perturbation is Underrated for Differentially Private Convex Optimization. CoRR (2019)
Qi Meng, Shuxin Zheng, Huishuai Zhang, Wei Chen, Qiwei Ye, Zhi-Ming Ma, Nenghai Yu, Tie-Yan Liu
G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space. ICLR (Poster) (2019)
Shuxin Zheng, Qi Meng, Huishuai Zhang, Wei Chen, Nenghai Yu, Tie-Yan Liu
Capacity Control of ReLU Neural Networks by Basis-Path Norm. AAAI (2019)
Shicong Cen, Huishuai Zhang, Yuejie Chi, Wei Chen, Tie-Yan Liu
Convergence of Distributed Stochastic Variance Reduced Methods without Sampling Extra Data. CoRR (2019)
Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
BN-invariant Sharpness Regularizes the Training Model to Better Generalization. IJCAI (2019)
Qi Meng, Wei Chen, Yue Wang, Zhi-Ming Ma, Tie-Yan Liu
Convergence analysis of distributed stochastic gradient descent with shuffling. Neurocomputing 337 (2019)
Ling Pan, Qingpeng Cai, Qi Meng, Wei Chen, Longbo Huang, Tie-Yan Liu
Reinforcement Learning with Dynamic Boltzmann Softmax Updates. CoRR (2019)
Mingyang Yi, Qi Meng, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
Positively Scale-Invariant Flatness of ReLU Neural Networks. CoRR (2019)
Xiaowei Chen, Weiran Huang, Wei Chen, John C. S. Lui
Community Exploration: From Offline Optimization to Online Learning. NeurIPS (2018)
Yue Wang, Qi Meng, Wei Chen, Yuting Liu, Zhiming Ma, Tie-Yan Liu
Target Transfer Q-Learning and Its Convergence Analysis. CoRR (2018)
Zhuohan Li, Di He, Fei Tian, Wei Chen, Tao Qin, Liwei Wang, Tie-Yan Liu
Towards Binary-Valued Gates for Robust LSTM Training. ICML (2018)
Zhuohan Li, Di He, Fei Tian, Wei Chen, Tao Qin, Liwei Wang, Tie-Yan Liu
Towards Binary-Valued Gates for Robust LSTM Training. CoRR (2018)
Li He, Qi Meng, Wei Chen, Zhiming Ma, Tie-Yan Liu
Differential Equations for Modeling Asynchronous Algorithms. CoRR (2018)
Li He, Qi Meng, Wei Chen, Zhiming Ma, Tie-Yan Liu
Differential Equations for Modeling Asynchronous Algorithms. IJCAI (2018)
Xiaowei Chen, Weiran Huang, Wei Chen, John C. S. Lui
Community Exploration: From Offline Optimization to Online Learning. CoRR (2018)
Huishuai Zhang, Wei Chen, Tie-Yan Liu
On the Local Hessian in Back-propagation. NeurIPS (2018)
Shuxin Zheng, Qi Meng, Huishuai Zhang, Wei Chen, Nenghai Yu, Tie-Yan Liu
Capacity Control of ReLU Neural Networks by Basis-path Norm. CoRR (2018)
Huishuai Zhang, Wei Chen, Tie-Yan Liu
Train Feedfoward Neural Network with Layer-wise Adaptive Rate via Approximating Back-matching Propagation. CoRR (2018)
Qi Meng, Wei Chen, Shuxin Zheng, Qiwei Ye, Tie-Yan Liu
Optimizing Neural Networks in the Equivalent Class Space. CoRR (2018)
Yishi Lin, Wei Chen, John C. S. Lui
Boosting Information Spread: An Algorithmic Approach. IEEE Trans. Comput. Soc. Syst. 5 (2) (2018)
Yue Wang, Wei Chen, Yuting Liu, Zhi-Ming Ma, Tie-Yan Liu
Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting. CoRR (2018)
Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu
Slim-DP: A Multi-Agent System for Communication-Efficient Distributed Deep Learning. AAMAS (2018)
Yan Tong, Jian Zhang, Wei Chen, Mingdi Xu, Tao Qin
Dynamic Group Behavior Analysis and Its Application in Network Abnormal Behavior Detection. ChinaCom (2) (2017)
Qi Meng, Wei Chen, Yue Wang, Zhiming Ma, Tie-Yan Liu
Convergence Analysis of Distributed Stochastic Gradient Descent with Shuffling. CoRR (2017)
Yishi Lin, Wei Chen, John C. S. Lui
Boosting Information Spread: An Algorithmic Approach. ICDE (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Wei Chen