Wei Chen - RankMe

168 papers A* 48A 10Journal 97Unranked 13

Year	Rank	Type	Title / Venue / Authors
2026	A	`conf`	How Do LLM-Generated Texts Impact Term-Based Retrieval Models? WSDM Wei Huang, Keping Bi, Yinqiong Cai, Wei Chen, Jiafeng Guo, Xueqi Cheng
2026	A*	`conf`	Rethinking Implicit Hate Speech Detection: Focusing on Latent Hate Components via Dual-Process Argumentation. WWW Shiqi Sun, Du Su, Wei Chen, Xueqi Cheng
2025	J	`jnl`	CAME: Competitively Learning a Mixture-of-Experts Model for First-stage Retrieval. ACM Trans. Inf. Syst. Jiafeng Guo, Yinqiong Cai, Keping Bi, Yixing Fan, Wei Chen, Ruqing Zhang, Xueqi Cheng
2025	A*	`conf`	CLIPure: Purification in Latent Space via CLIP for Adversarially Robust Zero-Shot Classification. ICLR Mingkun Zhang, Keping Bi, Wei Chen, Jiafeng Guo, Xueqi Cheng
2025	J	`jnl`	CLIPure: Purification in Latent Space via CLIP for Adversarially Robust Zero-Shot Classification. CoRR Mingkun Zhang, Keping Bi, Wei Chen, Jiafeng Guo, Xueqi Cheng
2025	J	`jnl`	Continuous K-Max Bandits. CoRR Yu Chen, Siwei Wang, Longbo Huang, Wei Chen
2025	—	`conf`	Evaluating Implicit Bias in Large Language Models by Attacking From a Psychometric Perspective. ACL (Findings) Yuchen Wen, Keping Bi, Wei Chen, Jiafeng Guo, Xueqi Cheng
2025	J	`jnl`	How Do LLM-Generated Texts Impact Term-Based Retrieval Models? CoRR Wei Huang, Keping Bi, Yinqiong Cai, Wei Chen, Jiafeng Guo, Xueqi Cheng
2024	J	`jnl`	A Unified Causal View of Instruction Tuning. CoRR Lu Chen, Wei Huang, Ruqing Zhang, Wei Chen, Jiafeng Guo, Xueqi Cheng
2024	A*	`conf`	CausalDiff: Causality-Inspired Disentanglement via Diffusion Model for Adversarial Defense. NeurIPS Mingkun Zhang, Keping Bi, Wei Chen, Quanrun Chen, Jiafeng Guo, Xueqi Cheng
2024	J	`jnl`	CausalDiff: Causality-Inspired Disentanglement via Diffusion Model for Adversarial Defense. CoRR Mingkun Zhang, Keping Bi, Wei Chen, Quanrun Chen, Jiafeng Guo, Xueqi Cheng
2024	A	`conf`	Classifier Guidance Enhances Diffusion-Based Adversarial Purification by Preserving Predictive Information. ECAI Mingkun Zhang, Jianing Li, Wei Chen, Jiafeng Guo, Xueqi Cheng
2024	J	`jnl`	Classifier Guidance Enhances Diffusion-based Adversarial Purification by Preserving Predictive Information. CoRR Mingkun Zhang, Jianing Li, Wei Chen, Jiafeng Guo, Xueqi Cheng
2024	J	`jnl`	Evaluating Implicit Bias in Large Language Models by Attacking From a Psychometric Perspective. CoRR Yuchen Wen, Keping Bi, Wei Chen, Jiafeng Guo, Xueqi Cheng
2024	A*	`conf`	Generative Retrieval Meets Multi-Graded Relevance. NeurIPS Yubao Tang, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Xueqi Cheng
2024	J	`jnl`	Generative Retrieval Meets Multi-Graded Relevance. CoRR Yubao Tang, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Xueqi Cheng
2024	J	`jnl`	Listwise Generative Retrieval Models via a Sequential Learning Process. CoRR Yubao Tang, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Xueqi Cheng
2024	J	`jnl`	Listwise Generative Retrieval Models via a Sequential Learning Process. ACM Trans. Inf. Syst. Yubao Tang, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Xueqi Cheng
2024	J	`jnl`	On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond. CoRR Bohan Wang, Huishuai Zhang, Qi Meng, Ruoyu Sun, Zhi-Ming Ma, Wei Chen
2024	A*	`conf`	Perturbation-Invariant Adversarial Training for Neural Ranking Models: Improving the Effectiveness-Robustness Trade-Off. AAAI Yu-An Liu, Ruqing Zhang, Mingkun Zhang, Wei Chen, Maarten de Rijke, Jiafeng Guo, Xueqi Cheng
2024	A*	`conf`	Provable Adaptivity of Adam under Non-uniform Smoothness. KDD Bohan Wang, Yushun Zhang, Huishuai Zhang, Qi Meng, Ruoyu Sun, Zhi-Ming Ma, Tie-Yan Liu, Zhi-Quan Luo, Wei Chen
2023	A	`conf`	Black-box Adversarial Attacks against Dense Retrieval Models: A Multi-view Contrastive Learning Method. CIKM Yu-An Liu, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Yixing Fan, Xueqi Cheng
2023	J	`jnl`	Black-box Adversarial Attacks against Dense Retrieval Models: A Multi-view Contrastive Learning Method. CoRR Yu-An Liu, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Yixing Fan, Xueqi Cheng
2023	J	`jnl`	CAME: Competitively Learning a Mixture-of-Experts Model for First-stage Retrieval. CoRR Yinqiong Cai, Yixing Fan, Keping Bi, Jiafeng Guo, Wei Chen, Ruqing Zhang, Xueqi Cheng
2023	J	`jnl`	Closing the Gap Between the Upper Bound and the Lower Bound of Adam's Iteration Complexity. CoRR Bohan Wang, Jingwen Fu, Huishuai Zhang, Nanning Zheng, Wei Chen
2023	A*	`conf`	Closing the gap between the upper bound and lower bound of Adam's iteration complexity. NeurIPS Bohan Wang, Jingwen Fu, Huishuai Zhang, Nanning Zheng, Wei Chen
2023	A*	`conf`	Collaborative Pure Exploration in Kernel Bandit. ICLR Yihan Du, Wei Chen, Yuko Kuroki, Longbo Huang
2023	A	`conf`	Continual Learning for Generative Retrieval over Dynamic Corpora. CIKM Jiangui Chen, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Yixing Fan, Xueqi Cheng
2023	J	`jnl`	Continual Learning for Generative Retrieval over Dynamic Corpora. CoRR Jiangui Chen, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Yixing Fan, Xueqi Cheng
2023	A*	`conf`	Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions. COLT Bohan Wang, Huishuai Zhang, Zhiming Ma, Wei Chen
2023	J	`jnl`	Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions. CoRR Bohan Wang, Huishuai Zhang, Zhi-Ming Ma, Wei Chen
2023	J	`jnl`	Incorporating NODE with pre-trained neural differential operator for learning dynamics. Neurocomputing Shiqi Gong, Qi Meng, Yue Wang, Lijun Wu, Wei Chen, Zhiming Ma, Tie-Yan Liu
2023	A	`conf`	Inducing Causal Structure for Abstractive Text Summarization. CIKM Lu Chen, Ruqing Zhang, Wei Huang, Wei Chen, Jiafeng Guo, Xueqi Cheng
2023	J	`jnl`	Inducing Causal Structure for Abstractive Text Summarization. CoRR Lu Chen, Ruqing Zhang, Wei Huang, Wei Chen, Jiafeng Guo, Xueqi Cheng
2023	A	`conf`	L2R: Lifelong Learning for First-stage Retrieval with Backward-Compatible Representations. CIKM Yinqiong Cai, Keping Bi, Yixing Fan, Jiafeng Guo, Wei Chen, Xueqi Cheng
2023	J	`jnl`	L^2R: Lifelong Learning for First-stage Retrieval with Backward-Compatible Representations. CoRR Yinqiong Cai, Keping Bi, Yixing Fan, Jiafeng Guo, Wei Chen, Xueqi Cheng
2023	J	`jnl`	On the Robustness of Generative Retrieval Models: An Out-of-Distribution Perspective. CoRR Yu-An Liu, Ruqing Zhang, Jiafeng Guo, Wei Chen, Xueqi Cheng
2023	J	`jnl`	Perturbation-Invariant Adversarial Training for Neural Ranking Models: Improving the Effectiveness-Robustness Trade-Off. CoRR Yu-An Liu, Ruqing Zhang, Mingkun Zhang, Wei Chen, Maarten de Rijke, Jiafeng Guo, Xueqi Cheng
2023	J	`jnl`	Power-law Dynamic arising from machine learning. CoRR Wei Chen, Weitao Du, Zhi-Ming Ma, Qi Meng
2023	A*	`conf`	Topic-oriented Adversarial Attacks against Black-box Neural Ranking Models. SIGIR Yu-An Liu, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Yixing Fan, Xueqi Cheng
2023	J	`jnl`	Topic-oriented Adversarial Attacks against Black-box Neural Ranking Models. CoRR Yu-An Liu, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Yixing Fan, Xueqi Cheng
2023	J	`jnl`	When and Why Momentum Accelerates SGD: An Empirical Study. CoRR Jingwen Fu, Bohan Wang, Huishuai Zhang, Zhizheng Zhang, Wei Chen, Nanning Zheng
2022	A*	`conf`	Availability Attacks Create Shortcuts. KDD Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
2022	J	`jnl`	Branching Reinforcement Learning. CoRR Yihan Du, Wei Chen
2022	A	`conf`	Certified Robustness to Word Substitution Ranking Attack for Neural Ranking Models. CIKM Chen Wu, Ruqing Zhang, Jiafeng Guo, Wei Chen, Yixing Fan, Maarten de Rijke, Xueqi Cheng
2022	J	`jnl`	Certified Robustness to Word Substitution Ranking Attack for Neural Ranking Models. CoRR Chen Wu, Ruqing Zhang, Jiafeng Guo, Wei Chen, Yixing Fan, Maarten de Rijke, Xueqi Cheng
2022	J	`jnl`	Constructing the Basis Path Set by Eliminating the Path Dependency. J. Syst. Sci. Complex. Juanping Zhu, Qi Meng, Wei Chen, Yue Wang, Zhiming Ma
2022	A*	`conf`	Does Momentum Change the Implicit Regularization on Separable Data? NeurIPS Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
2022	A*	`conf`	Gradient Information Matters in Policy Optimization by Back-propagating through Model. ICLR Chongchong Li, Yue Wang, Wei Chen, Yuting Liu, Zhi-Ming Ma, Tie-Yan Liu
2022	J	`jnl`	Neural Operator with Regularity Structure for Modeling Dynamics Driven by SPDEs. CoRR Peiyan Hu, Qi Meng, Bingguang Chen, Shiqi Gong, Yue Wang, Wei Chen, Rongchan Zhu, Zhi-Ming Ma, Tie-Yan Liu
2022	J	`jnl`	Normalized/Clipped SGD with Perturbation for Differentially Private Non-Convex Optimization. CoRR Xiaodong Yang, Huishuai Zhang, Wei Chen, Tie-Yan Liu
2022	A*	`conf`	PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior. ICLR Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu
2022	J	`jnl`	Provable Adaptivity in Adam. CoRR Bohan Wang, Yushun Zhang, Huishuai Zhang, Qi Meng, Zhi-Ming Ma, Tie-Yan Liu, Wei Chen
2022	A*	`conf`	SE(3) Equivariant Graph Neural Networks with Complete Local Frames. ICML Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Nanning Zheng, Bin Shao, Tie-Yan Liu
2022	J	`jnl`	Stabilize deep ResNet with a sharp scaling factor τ. Mach. Learn. Huishuai Zhang, Da Yu, Mingyang Yi, Wei Chen, Tie-Yan Liu
2022	A*	`conf`	Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret. NeurIPS Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu
2022	J	`jnl`	Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret. CoRR Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu
2022	A*	`conf`	Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart. CVPR Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu
2021	J	`jnl`	Adversarial Training with Rectified Rejection. CoRR Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu
2021	J	`jnl`	BN-invariant sharpness regularizes the training model to better generalization. CoRR Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
2021	J	`jnl`	Causally Invariant Predictor with Shift-Robustness. CoRR Xiangyu Zheng, Xinwei Sun, Wei Chen, Tie-Yan Liu
2021	—	`conf`	CoMAE: A Multi-factor Hierarchical Framework for Empathetic Response Generation. ACL/IJCNLP (Findings) Chujie Zheng, Yong Liu, Wei Chen, Yongcai Leng, Minlie Huang
2021	J	`jnl`	CoMAE: A Multi-factor Hierarchical Framework for Empathetic Response Generation. CoRR Chujie Zheng, Yong Liu, Wei Chen, Yongcai Leng, Minlie Huang
2021	J	`jnl`	Collaborative Pure Exploration in Kernel Bandit. CoRR Yihan Du, Wei Chen, Yuko Kuroki, Longbo Huang
2021	J	`jnl`	Combinatorial Pure Exploration with Bottleneck Reward Function and its Extension to General Reward Functions. CoRR Yihan Du, Yuko Kuroki, Wei Chen
2021	A*	`conf`	Combinatorial Pure Exploration with Full-Bandit or Partial Linear Feedback. AAAI Yihan Du, Yuko Kuroki, Wei Chen
2021	J	`jnl`	Do Not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning. CoRR Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu
2021	A*	`conf`	Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning. ICLR Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu
2021	—	`conf`	EARL: Informative Knowledge-Grounded Conversation Generation with Entity-Agnostic Representation Learning. EMNLP (1) Hao Zhou, Minlie Huang, Yong Liu, Wei Chen, Xiaoyan Zhu
2021	J	`jnl`	Equivariant vector field network for many-body system modeling. CoRR Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Bin Shao, Tie-Yan Liu
2021	A*	`conf`	How Does Data Augmentation Affect Privacy in Machine Learning? AAAI Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
2021	J	`jnl`	Incorporating NODE with Pre-trained Neural Differential Operator for Learning Dynamics. CoRR Shiqi Gong, Qi Meng, Yue Wang, Lijun Wu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
2021	J	`jnl`	Indiscriminate Poisoning Attacks Are Shortcuts. CoRR Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
2021	J	`jnl`	Interpreting the Basis Path Set in Neural Networks. J. Syst. Sci. Complex. Juanping Zhu, Qi Meng, Wei Chen, Zhiming Ma
2021	A*	`conf`	Large Scale Private Learning via Low-rank Reparametrization. ICML Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
2021	J	`jnl`	Large Scale Private Learning via Low-rank Reparametrization. CoRR Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
2021	A*	`conf`	Learning Causal Semantic Representation for Out-of-Distribution Prediction. NeurIPS Chang Liu, Xinwei Sun, Jindong Wang, Haoyue Tang, Tao Li, Tao Qin, Wei Chen, Tie-Yan Liu
2021	J	`jnl`	Machine-Learning Non-Conservative Dynamics for New-Physics Detection. CoRR Ziming Liu, Bohan Wang, Qi Meng, Wei Chen, Max Tegmark, Tie-Yan Liu
2021	J	`jnl`	Momentum Doesn't Change the Implicit Bias. CoRR Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma
2021	A*	`conf`	Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD. NeurIPS Bohan Wang, Huishuai Zhang, Jieyu Zhang, Qi Meng, Wei Chen, Tie-Yan Liu
2021	J	`jnl`	Optimizing Information-theoretical Generalization Bounds via Anisotropic Noise in SGLD. CoRR Bohan Wang, Huishuai Zhang, Jieyu Zhang, Qi Meng, Wei Chen, Tie-Yan Liu
2021	A	`conf`	Path-BN: Towards effective batch normalization in the Path Space for ReLU networks. UAI Xufang Luo, Qi Meng, Wei Chen, Yunhong Wang, Tie-Yan Liu
2021	J	`jnl`	PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Driven Adaptive Prior. CoRR Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu
2021	A*	`conf`	R-Drop: Regularized Dropout for Neural Networks. NeurIPS Xiaobo Liang, Lijun Wu, Juntao Li, Yue Wang, Qi Meng, Tao Qin, Wei Chen, Min Zhang, Tie-Yan Liu
2021	J	`jnl`	R-Drop: Regularized Dropout for Neural Networks. CoRR Xiaobo Liang, Lijun Wu, Juntao Li, Yue Wang, Qi Meng, Tao Qin, Wei Chen, Min Zhang, Tie-Yan Liu
2021	A*	`conf`	Recovering Latent Causal Factor for Generalization to Distributional Shifts. NeurIPS Xinwei Sun, Botong Wu, Xiangyu Zheng, Chang Liu, Wei Chen, Tao Qin, Tie-Yan Liu
2021	J	`jnl`	Regularized OFU: an Efficient UCB Estimator forNon-linear Contextual Bandit. CoRR Yichi Zhou, Shihong Song, Huishuai Zhang, Jun Zhu, Wei Chen, Tie-Yan Liu
2021	A*	`conf`	The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks. ICML Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu
2021	J	`jnl`	Towards Accelerating Training of Batch Normalization: A Manifold Perspective. CoRR Mingyang Yi, Qi Meng, Wei Chen, Zhi-Ming Ma
2020	A*	`conf`	(Locally) Differentially Private Combinatorial Semi-Bandits. ICML Xiaoyu Chen, Kai Zheng, Zixin Zhou, Yunchang Yang, Wei Chen, Liwei Wang
2020	J	`jnl`	(Locally) Differentially Private Combinatorial Semi-Bandits. CoRR Xiaoyu Chen, Kai Zheng, Zixin Zhou, Yunchang Yang, Wei Chen, Liwei Wang
2020	A*	`conf`	Combinatorial Pure Exploration for Dueling Bandit. ICML Wei Chen, Yihan Du, Longbo Huang, Haoyu Zhao
2020	J	`jnl`	Combinatorial Pure Exploration of Dueling Bandit. CoRR Wei Chen, Yihan Du, Longbo Huang, Haoyu Zhao
2020	J	`jnl`	Combinatorial Pure Exploration with Partial or Full-Bandit Linear Feedback. CoRR Wei Chen, Yihan Du, Yuko Kuroki
2020	J	`jnl`	Combinatorial Semi-Bandit in the Non-Stationary Environment. CoRR Wei Chen, Liwei Wang, Haoyu Zhao, Kai Zheng
2020	J	`jnl`	Constructing Basis Path Set by Eliminating Path Dependency. CoRR Juanping Zhu, Qi Meng, Wei Chen, Yue Wang, Zhiming Ma
2020	J	`jnl`	Convergence of Distributed Stochastic Variance Reduced Methods Without Sampling Extra Data. IEEE Trans. Signal Process. Shicong Cen, Huishuai Zhang, Yuejie Chi, Wei Chen, Tie-Yan Liu
2020	J	`jnl`	Dynamic of Stochastic Gradient Descent with State-Dependent Noise. CoRR Qi Meng, Shiqi Gong, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
2020	A*	`conf`	Gradient Perturbation is Underrated for Differentially Private Convex Optimization. IJCAI Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
2020	A*	`conf`	I4R: Promoting Deep Reinforcement Learning by the Indicator for Expressive Representations. IJCAI Xufang Luo, Qi Meng, Di He, Wei Chen, Yunhong Wang
2020	J	`jnl`	Identifying Invariant Texture Violation for Robust Deepfake Detection. CoRR Xinwei Sun, Botong Wu, Wei Chen
2020	J	`jnl`	Latent Causal Invariant Model. CoRR Xinwei Sun, Botong Wu, Chang Liu, Xiangyu Zheng, Wei Chen, Tao Qin, Tie-Yan Liu
2020	J	`jnl`	Learning Causal Semantic Representation for Out-of-Distribution Prediction. CoRR Chang Liu, Xinwei Sun, Jindong Wang, Tao Li, Tao Qin, Wei Chen, Tie-Yan Liu
2020	J	`jnl`	Membership Inference with Privately Augmented Data Endorses the Benign while Suppresses the Adversary. CoRR Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
2020	A*	`conf`	Reinforcement Learning with Dynamic Boltzmann Softmax Updates. IJCAI Ling Pan, Qingpeng Cai, Qi Meng, Wei Chen, Longbo Huang
2020	J	`jnl`	Target transfer Q-learning and its convergence analysis. Neurocomputing Yue Wang, Yuting Liu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
2020	J	`jnl`	The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks. CoRR Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu
2019	A*	`conf`	BN-invariant Sharpness Regularizes the Training Model to Better Generalization. IJCAI Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
2019	A*	`conf`	Capacity Control of ReLU Neural Networks by Basis-Path Norm. AAAI Shuxin Zheng, Qi Meng, Huishuai Zhang, Wei Chen, Nenghai Yu, Tie-Yan Liu
2019	J	`jnl`	Convergence analysis of distributed stochastic gradient descent with shuffling. Neurocomputing Qi Meng, Wei Chen, Yue Wang, Zhi-Ming Ma, Tie-Yan Liu
2019	J	`jnl`	Convergence of Distributed Stochastic Variance Reduced Methods without Sampling Extra Data. CoRR Shicong Cen, Huishuai Zhang, Yuejie Chi, Wei Chen, Tie-Yan Liu
2019	—	`conf`	G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space. ICLR (Poster) Qi Meng, Shuxin Zheng, Huishuai Zhang, Wei Chen, Qiwei Ye, Zhi-Ming Ma, Nenghai Yu, Tie-Yan Liu
2019	J	`jnl`	Gradient Perturbation is Underrated for Differentially Private Convex Optimization. CoRR Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu, Jian Yin
2019	J	`jnl`	Interpreting Basis Path Set in Neural Networks. CoRR Juanping Zhu, Qi Meng, Wei Chen, Zhiming Ma
2019	J	`jnl`	OptQuant: Distributed training of neural networks with optimized quantization mechanisms. Neurocomputing Li He, Shuxin Zheng, Wei Chen, Zhiming Ma, Tie-Yan Liu
2019	J	`jnl`	Positively Scale-Invariant Flatness of ReLU Neural Networks. CoRR Mingyang Yi, Qi Meng, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
2019	J	`jnl`	Reinforcement Learning with Dynamic Boltzmann Softmax Updates. CoRR Ling Pan, Qingpeng Cai, Qi Meng, Wei Chen, Longbo Huang, Tie-Yan Liu
2019	J	`jnl`	Training Over-parameterized Deep ResNet Is almost as Easy as Training a Two-layer Network. CoRR Huishuai Zhang, Da Yu, Wei Chen, Tie-Yan Liu
2018	J	`jnl`	Capacity Control of ReLU Neural Networks by Basis-path Norm. CoRR Shuxin Zheng, Qi Meng, Huishuai Zhang, Wei Chen, Nenghai Yu, Tie-Yan Liu
2018	A*	`conf`	Differential Equations for Modeling Asynchronous Algorithms. IJCAI Li He, Qi Meng, Wei Chen, Zhiming Ma, Tie-Yan Liu
2018	J	`jnl`	Differential Equations for Modeling Asynchronous Algorithms. CoRR Li He, Qi Meng, Wei Chen, Zhiming Ma, Tie-Yan Liu
2018	J	`jnl`	Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting. CoRR Yue Wang, Wei Chen, Yuting Liu, Zhi-Ming Ma, Tie-Yan Liu
2018	A*	`conf`	On the Local Hessian in Back-propagation. NeurIPS Huishuai Zhang, Wei Chen, Tie-Yan Liu
2018	J	`jnl`	Optimizing Neural Networks in the Equivalent Class Space. CoRR Qi Meng, Wei Chen, Shuxin Zheng, Qiwei Ye, Tie-Yan Liu
2018	A	`conf`	Slim-DP: A Multi-Agent System for Communication-Efficient Distributed Deep Learning. AAMAS Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu
2018	J	`jnl`	Target Transfer Q-Learning and Its Convergence Analysis. CoRR Yue Wang, Qi Meng, Wei Chen, Yuting Liu, Zhiming Ma, Tie-Yan Liu
2018	A*	`conf`	Towards Binary-Valued Gates for Robust LSTM Training. ICML Zhuohan Li, Di He, Fei Tian, Wei Chen, Tao Qin, Liwei Wang, Tie-Yan Liu
2018	J	`jnl`	Towards Binary-Valued Gates for Robust LSTM Training. CoRR Zhuohan Li, Di He, Fei Tian, Wei Chen, Tao Qin, Liwei Wang, Tie-Yan Liu
2018	J	`jnl`	Train Feedfoward Neural Network with Layer-wise Adaptive Rate via Approximating Back-matching Propagation. CoRR Huishuai Zhang, Wei Chen, Tie-Yan Liu
2018	J	`jnl`	基于BiLSTM-CRF的关键词自动抽取 (Automatic Keyword Extraction Based on BiLSTM-CRF). 计算机科学 Wei Chen, Youzheng Wu, Wenliang Chen, Min Zhang
2017	A*	`conf`	Asynchronous Stochastic Gradient Descent with Delay Compensation. ICML Shuxin Zheng, Qi Meng, Taifeng Wang, Wei Chen, Nenghai Yu, Zhiming Ma, Tie-Yan Liu
2017	A*	`conf`	Asynchronous Stochastic Proximal Optimization Algorithms with Variance Reduction. AAAI Qi Meng, Wei Chen, Jingcheng Yu, Taifeng Wang, Zhiming Ma, Tie-Yan Liu
2017	J	`jnl`	Convergence Analysis of Distributed Stochastic Gradient Descent with Shuffling. CoRR Qi Meng, Wei Chen, Yue Wang, Zhiming Ma, Tie-Yan Liu
2017	—	`conf`	Distributed Machine Learning: Foundations, Trends, and Practices. WWW (Companion Volume) Tie-Yan Liu, Wei Chen, Taifeng Wang
2017	A*	`conf`	Dual Supervised Learning. ICML Yingce Xia, Tao Qin, Wei Chen, Jiang Bian, Nenghai Yu, Tie-Yan Liu
2017	J	`jnl`	Dual Supervised Learning. CoRR Yingce Xia, Tao Qin, Wei Chen, Jiang Bian, Nenghai Yu, Tie-Yan Liu
2017	—	`conf`	Dynamic Group Behavior Analysis and Its Application in Network Abnormal Behavior Detection. ChinaCom (2) Yan Tong, Jian Zhang, Wei Chen, Mingdi Xu, Tao Qin
2017	A*	`conf`	Efficient Inexact Proximal Gradient Algorithm for Nonconvex Problems. IJCAI Quanming Yao, James T. Kwok, Fei Gao, Wei Chen, Tie-Yan Liu
2017	—	`conf`	Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks. ECML/PKDD (1) Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu
2017	—	`conf`	Finite sample analysis of the GTD Policy Evaluation Algorithms in Markov Setting. NIPS Yue Wang, Wei Chen, Yuting Liu, Zhiming Ma, Tie-Yan Liu
2017	A*	`conf`	Generalization Error Bounds for Optimization Algorithms via Stability. AAAI Qi Meng, Yue Wang, Wei Chen, Taifeng Wang, Zhiming Ma, Tie-Yan Liu
2017	—	`conf`	LightGBM: A Highly Efficient Gradient Boosting Decision Tree. NIPS Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, Tie-Yan Liu
2017	J	`jnl`	Slim-DP: A Light Communication Data Parallelism for DNN. CoRR Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu
2016	—	`conf`	A Communication-Efficient Parallel Algorithm for Decision Tree. NIPS Qi Meng, Guolin Ke, Taifeng Wang, Wei Chen, Qiwei Ye, Zhiming Ma, Tie-Yan Liu
2016	J	`jnl`	A Communication-Efficient Parallel Algorithm for Decision Tree. CoRR Qi Meng, Guolin Ke, Taifeng Wang, Wei Chen, Qiwei Ye, Zhiming Ma, Tie-Yan Liu
2016	A*	`conf`	Asynchronous Accelerated Stochastic Gradient Descent. IJCAI Qi Meng, Wei Chen, Jingcheng Yu, Taifeng Wang, Zhiming Ma, Tie-Yan Liu
2016	J	`jnl`	Asynchronous Stochastic Gradient Descent with Delay Compensation for Distributed Deep Learning. CoRR Shuxin Zheng, Qi Meng, Taifeng Wang, Wei Chen, Nenghai Yu, Zhiming Ma, Tie-Yan Liu
2016	J	`jnl`	Asynchronous Stochastic Proximal Optimization Algorithms with Variance Reduction. CoRR Qi Meng, Wei Chen, Jingcheng Yu, Taifeng Wang, Zhiming Ma, Tie-Yan Liu
2016	J	`jnl`	Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks. CoRR Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu
2016	J	`jnl`	Generalization Error Bounds for Optimization Algorithms via Stability. CoRR Qi Meng, Yue Wang, Wei Chen, Taifeng Wang, Zhiming Ma, Tie-Yan Liu
2016	A*	`conf`	On the Depth of Deep Neural Networks: A Theoretical View. AAAI Shizhao Sun, Wei Chen, Liwei Wang, Xiaoguang Liu, Tie-Yan Liu
2015	A*	`conf`	Generalization Analysis for Game-Theoretic Machine Learning. AAAI Haifang Li, Fei Tian, Wei Chen, Tao Qin, Zhiming Ma, Tie-Yan Liu
2015	J	`jnl`	Large Margin Deep Neural Networks: Theory and Algorithms. CoRR Shizhao Sun, Wei Chen, Liwei Wang, Tie-Yan Liu
2015	A*	`conf`	Mechanism Learning with Mechanism Induced Data. AAAI Tie-Yan Liu, Wei Chen, Tao Qin
2014	J	`jnl`	A Game-theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search. CoRR Di He, Wei Chen, Liwei Wang, Tie-Yan Liu
2014	A*	`conf`	Agent Behavior Prediction and Its Generalization Analysis. AAAI Fei Tian, Haifang Li, Wei Chen, Tao Qin, Enhong Chen, Tie-Yan Liu
2014	J	`jnl`	Agent Behavior Prediction and Its Generalization Analysis. CoRR Fei Tian, Haifang Li, Wei Chen, Tao Qin, Enhong Chen, Tie-Yan Liu
2014	J	`jnl`	Generalization Analysis for Game-Theoretic Machine Learning. CoRR Haifang Li, Fei Tian, Wei Chen, Tao Qin, Tie-Yan Liu
2014	J	`jnl`	Generalized Second Price Auction with Probabilistic Broad Match. CoRR Wei Chen, Di He, Tie-Yan Liu, Tao Qin, Yixin Tao, Liwei Wang
2014	A*	`conf`	Generalized second price auction with probabilistic broad match. EC Wei Chen, Di He, Tie-Yan Liu, Tao Qin, Yixin Tao, Liwei Wang
2014	A	`conf`	Sampling dilemma: towards effective data sampling for click prediction in sponsored search. WSDM Jun Feng, Jiang Bian, Taifeng Wang, Wei Chen, Xiaoyan Zhu, Tie-Yan Liu
2014	J	`jnl`	Sponsored Search Auctions: Recent Advances and Future Directions. ACM Trans. Intell. Syst. Technol. Tao Qin, Wei Chen, Tie-Yan Liu
2013	A*	`conf`	A Game-Theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search. IJCAI Di He, Wei Chen, Liwei Wang, Tie-Yan Liu
2013	J	`jnl`	A Theoretical Analysis of NDCG Type Ranking Measures CoRR Yining Wang, Liwei Wang, Yuanzhi Li, Di He, Tie-Yan Liu, Wei Chen
2013	J	`jnl`	Online learning for auction mechanism in bandit setting. Decis. Support Syst. Di He, Wei Chen, Liwei Wang, Tie-Yan Liu
2012	—	`conf`	Convergence Analysis for Weighted Joint Strategy Fictitious Play in Generalized Second Price Auction. WINE Lei Yao, Wei Chen, Tie-Yan Liu
2010	—	`conf`	Two-Layer Generalization Analysis for Ranking Using Rademacher Average. NIPS Wei Chen, Tie-Yan Liu, Zhiming Ma
2009	—	`conf`	Ranking Measures and Loss Functions in Learning to Rank. NIPS Wei Chen, Tie-Yan Liu, Yanyan Lan, Zhiming Ma, Hang Li