Wei Chen

According to our database, Wei Chen authored at least 111 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond.

Bohan Wang, Huishuai Zhang, Qi Meng, Ruoyu Sun, Zhi-Ming Ma, Wei Chen

CoRR, 2024

Listwise Generative Retrieval Models via a Sequential Learning Process.

Yubao Tang, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Xueqi Cheng

CoRR, 2024

A Unified Causal View of Instruction Tuning.

Lu Chen, Wei Huang, Ruqing Zhang, Wei Chen, Jiafeng Guo, Xueqi Cheng

CoRR, 2024

Perturbation-Invariant Adversarial Training for Neural Ranking Models: Improving the Effectiveness-Robustness Trade-Off.

Yu-An Liu, Ruqing Zhang, Mingkun Zhang, Wei Chen, Maarten de Rijke, Jiafeng Guo, Xueqi Cheng

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Incorporating NODE with pre-trained neural differential operator for learning dynamics.

Shiqi Gong, Qi Meng, Yue Wang, Lijun Wu, Wei Chen, Zhiming Ma, Tie-Yan Liu

Neurocomputing, April, 2023

CAME: Competitively Learning a Mixture-of-Experts Model for First-stage Retrieval.

Yinqiong Cai, Yixing Fan, Keping Bi, Jiafeng Guo, Wei Chen, Ruqing Zhang, Xueqi Cheng

CoRR, 2023

On the Robustness of Generative Retrieval Models: An Out-of-Distribution Perspective.

Yu-An Liu, Ruqing Zhang, Jiafeng Guo, Wei Chen, Xueqi Cheng

CoRR, 2023

Power-law Dynamic arising from machine learning.

Wei Chen, Weitao Du, Zhi-Ming Ma, Qi Meng

CoRR, 2023

When and Why Momentum Accelerates SGD: An Empirical Study.

Jingwen Fu, Bohan Wang, Huishuai Zhang, Zhizheng Zhang, Wei Chen, Nanning Zheng

CoRR, 2023

Topic-oriented Adversarial Attacks against Black-box Neural Ranking Models.

Yu-An Liu, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Yixing Fan, Xueqi Cheng

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Closing the gap between the upper bound and lower bound of Adam's iteration complexity.

Bohan Wang, Jingwen Fu, Huishuai Zhang, Nanning Zheng, Wei Chen

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Collaborative Pure Exploration in Kernel Bandit.

Yihan Du, Wei Chen, Yuko Kuroki, Longbo Huang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions.

Bohan Wang, Huishuai Zhang, Zhiming Ma, Wei Chen

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Black-box Adversarial Attacks against Dense Retrieval Models: A Multi-view Contrastive Learning Method.

Yu-An Liu, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Yixing Fan, Xueqi Cheng

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Inducing Causal Structure for Abstractive Text Summarization.

Lu Chen, Ruqing Zhang, Wei Huang, Wei Chen, Jiafeng Guo, Xueqi Cheng

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Continual Learning for Generative Retrieval over Dynamic Corpora.

Jiangui Chen, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Yixing Fan, Xueqi Cheng

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

Stabilize deep ResNet with a sharp scaling factor τ.

Huishuai Zhang, Da Yu, Mingyang Yi, Wei Chen, Tie-Yan Liu

Mach. Learn., 2022

Constructing the Basis Path Set by Eliminating the Path Dependency.

Juanping Zhu, Qi Meng, Wei Chen, Yue Wang, Zhiming Ma

J. Syst. Sci. Complex., 2022

Provable Adaptivity in Adam.

Bohan Wang, Yushun Zhang, Huishuai Zhang, Qi Meng, Zhi-Ming Ma, Tie-Yan Liu, Wei Chen

CoRR, 2022

Normalized/Clipped SGD with Perturbation for Differentially Private Non-Convex Optimization.

Xiaodong Yang, Huishuai Zhang, Wei Chen, Tie-Yan Liu

CoRR, 2022

Neural Operator with Regularity Structure for Modeling Dynamics Driven by SPDEs.

Peiyan Hu, Qi Meng, Bingguang Chen, Shiqi Gong, Yue Wang, Wei Chen, Rongchan Zhu, Zhi-Ming Ma, Tie-Yan Liu

CoRR, 2022

Branching Reinforcement Learning.

Yihan Du, Wei Chen

CoRR, 2022

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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 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 Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Availability Attacks Create Shortcuts.

Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

SE(3) Equivariant Graph Neural Networks with Complete Local Frames.

Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Nanning Zheng, Bin Shao, Tie-Yan Liu

Proceedings of the International Conference on Machine Learning, 2022

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

Proceedings of the Tenth International Conference on Learning Representations, 2022

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

Proceedings of the Tenth International Conference on Learning Representations, 2022

Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart.

Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Certified Robustness to Word Substitution Ranking Attack for Neural Ranking Models.

Chen Wu, Ruqing Zhang, Jiafeng Guo, Wei Chen, Yixing Fan, Maarten de Rijke, Xueqi Cheng

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

Interpreting the Basis Path Set in Neural Networks.

Juanping Zhu, Qi Meng, Wei Chen, Zhiming Ma

J. Syst. Sci. Complex., 2021

Indiscriminate Poisoning Attacks Are Shortcuts.

Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu

CoRR, 2021

Equivariant vector field network for many-body system modeling.

Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Bin Shao, Tie-Yan Liu

CoRR, 2021

Optimizing Information-theoretical Generalization Bounds via Anisotropic Noise in SGLD.

Bohan Wang, Huishuai Zhang, Jieyu Zhang, Qi Meng, Wei Chen, Tie-Yan Liu

CoRR, 2021

Momentum Doesn't Change the Implicit Bias.

Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma

CoRR, 2021

Causally Invariant Predictor with Shift-Robustness.

Xiangyu Zheng, Xinwei Sun, Wei Chen, Tie-Yan Liu

CoRR, 2021

Regularized OFU: an Efficient UCB Estimator forNon-linear Contextual Bandit.

Yichi Zhou, Shihong Song, Huishuai Zhang, Jun Zhu, Wei Chen, Tie-Yan Liu

CoRR, 2021

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

Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu

CoRR, 2021

Machine-Learning Non-Conservative Dynamics for New-Physics Detection.

Ziming Liu, Bohan Wang, Qi Meng, Wei Chen, Max Tegmark, Tie-Yan Liu

CoRR, 2021

Adversarial Training with Rectified Rejection.

Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu

CoRR, 2021

Combinatorial Pure Exploration with Bottleneck Reward Function and its Extension to General Reward Functions.

Yihan Du, Yuko Kuroki, Wei Chen

CoRR, 2021

Towards Accelerating Training of Batch Normalization: A Manifold Perspective.

Mingyang Yi, Qi Meng, Wei Chen, Zhi-Ming Ma

CoRR, 2021

Path-BN: Towards effective batch normalization in the Path Space for ReLU networks.

Xufang Luo, Qi Meng, Wei Chen, Yunhong Wang, Tie-Yan Liu

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD.

Bohan Wang, Huishuai Zhang, Jieyu Zhang, Qi Meng, Wei Chen, Tie-Yan Liu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Large Scale Private Learning via Low-rank Reparametrization.

Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu

Proceedings of the 38th International Conference on Machine Learning, 2021

The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks.

Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu

Proceedings of the 38th International Conference on Machine Learning, 2021

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

Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu

Proceedings of the 9th International Conference on Learning Representations, 2021

How Does Data Augmentation Affect Privacy in Machine Learning?

Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Combinatorial Pure Exploration with Full-Bandit or Partial Linear Feedback.

Yihan Du, Yuko Kuroki, Wei Chen

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Convergence of Distributed Stochastic Variance Reduced Methods Without Sampling Extra Data.

Shicong Cen, Huishuai Zhang, Yuejie Chi, Wei Chen, Tie-Yan Liu

IEEE Trans. Signal Process., 2020

Target transfer Q-learning and its convergence analysis.

Yue Wang, Yuting Liu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

Neurocomputing, 2020

Identifying Invariant Texture Violation for Robust Deepfake Detection.

Xinwei Sun, Botong Wu, Wei Chen

CoRR, 2020

The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks.

Bohan Wang, Qi Meng, Wei Chen

CoRR, 2020

Latent Causal Invariant Model.

Xinwei Sun, Botong Wu, Chang Liu, Xiangyu Zheng, Wei Chen, Tao Qin, Tie-Yan Liu

CoRR, 2020

Learning Causal Semantic Representation for Out-of-Distribution Prediction.

Chang Liu, Xinwei Sun, Jindong Wang, Tao Li, Tao Qin, Wei Chen, Tie-Yan Liu

CoRR, 2020

Membership Inference with Privately Augmented Data Endorses the Benign while Suppresses the Adversary.

Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu

CoRR, 2020

Dynamic of Stochastic Gradient Descent with State-Dependent Noise.

Qi Meng, Shiqi Gong, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

CoRR, 2020

Combinatorial Pure Exploration with Partial or Full-Bandit Linear Feedback.

Wei Chen, Yihan Du, Yuko Kuroki

CoRR, 2020

Combinatorial Semi-Bandit in the Non-Stationary Environment.

Wei Chen, Liwei Wang, Haoyu Zhao, Kai Zheng

CoRR, 2020

Gradient Perturbation is Underrated for Differentially Private Convex Optimization.

Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Reinforcement Learning with Dynamic Boltzmann Softmax Updates.

Ling Pan, Qingpeng Cai, Qi Meng, Wei Chen, Longbo Huang

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

I4R: Promoting Deep Reinforcement Learning by the Indicator for Expressive Representations.

Xufang Luo, Qi Meng, Di He, Wei Chen, Yunhong Wang

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

(Locally) Differentially Private Combinatorial Semi-Bandits.

Xiaoyu Chen, Kai Zheng, Zixin Zhou, Yunchang Yang, Wei Chen, Liwei Wang

Proceedings of the 37th International Conference on Machine Learning, 2020

Combinatorial Pure Exploration for Dueling Bandit.

Wei Chen, Yihan Du, Longbo Huang, Haoyu Zhao

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Convergence analysis of distributed stochastic gradient descent with shuffling.

Qi Meng, Wei Chen, Yue Wang, Zhi-Ming Ma, Tie-Yan Liu

Neurocomputing, 2019

OptQuant: Distributed training of neural networks with optimized quantization mechanisms.

Li He, Shuxin Zheng, Wei Chen, Zhiming Ma, Tie-Yan Liu

Neurocomputing, 2019

Training Over-parameterized Deep ResNet Is almost as Easy as Training a Two-layer Network.

Huishuai Zhang, Da Yu, Wei Chen, Tie-Yan Liu

CoRR, 2019

Reinforcement Learning with Dynamic Boltzmann Softmax Updates.

Ling Pan, Qingpeng Cai, Qi Meng, Wei Chen, Longbo Huang, Tie-Yan Liu

CoRR, 2019

Positively Scale-Invariant Flatness of ReLU Neural Networks.

Mingyang Yi, Qi Meng, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

CoRR, 2019

BN-invariant Sharpness Regularizes the Training Model to Better Generalization.

Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space.

Qi Meng, Shuxin Zheng, Huishuai Zhang, Wei Chen, Qiwei Ye, Zhi-Ming Ma, Nenghai Yu, Tie-Yan Liu

Proceedings of the 7th International Conference on Learning Representations, 2019

Capacity Control of ReLU Neural Networks by Basis-Path Norm.

Shuxin Zheng, Qi Meng, Huishuai Zhang, Wei Chen, Nenghai Yu, Tie-Yan Liu

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Target Transfer Q-Learning and Its Convergence Analysis.

Yue Wang, Qi Meng, Wei Chen, Yuting Liu, Zhiming Ma, Tie-Yan Liu

CoRR, 2018

Train Feedfoward Neural Network with Layer-wise Adaptive Rate via Approximating Back-matching Propagation.

Huishuai Zhang, Wei Chen, Tie-Yan Liu

CoRR, 2018

Optimizing Neural Networks in the Equivalent Class Space.

Qi Meng, Wei Chen, Shuxin Zheng, Qiwei Ye, Tie-Yan Liu

CoRR, 2018

On the Local Hessian in Back-propagation.

Huishuai Zhang, Wei Chen, Tie-Yan Liu

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Differential Equations for Modeling Asynchronous Algorithms.

Li He, Qi Meng, Wei Chen, Zhiming Ma, Tie-Yan Liu

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Towards Binary-Valued Gates for Robust LSTM Training.

Zhuohan Li, Di He, Fei Tian, Wei Chen, Tao Qin, Liwei Wang, Tie-Yan Liu

Proceedings of the 35th International Conference on Machine Learning, 2018

Slim-DP: A Multi-Agent System for Communication-Efficient Distributed Deep Learning.

Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu

Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

2017

Slim-DP: A Light Communication Data Parallelism for DNN.

Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu

CoRR, 2017

Distributed Machine Learning: Foundations, Trends, and Practices.

Tie-Yan Liu, Wei Chen, Taifeng Wang

Proceedings of the 26th International Conference on World Wide Web Companion, 2017

Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks.

Shizhao Sun, Wei Chen, Jiang Bian, Xiaoguang Liu, Tie-Yan Liu

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Finite sample analysis of the GTD Policy Evaluation Algorithms in Markov Setting.

Yue Wang, Wei Chen, Yuting Liu, Zhiming Ma, Tie-Yan Liu

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

LightGBM: A Highly Efficient Gradient Boosting Decision Tree.

Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, Tie-Yan Liu

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Efficient Inexact Proximal Gradient Algorithm for Nonconvex Problems.

Quanming Yao, James T. Kwok, Fei Gao, Wei Chen, Tie-Yan Liu

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Asynchronous Stochastic Gradient Descent with Delay Compensation.

Shuxin Zheng, Qi Meng, Taifeng Wang, Wei Chen, Nenghai Yu, Zhiming Ma, Tie-Yan Liu

Proceedings of the 34th International Conference on Machine Learning, 2017

Dual Supervised Learning.

Yingce Xia, Tao Qin, Wei Chen, Jiang Bian, Nenghai Yu, Tie-Yan Liu

Proceedings of the 34th International Conference on Machine Learning, 2017

Dynamic Group Behavior Analysis and Its Application in Network Abnormal Behavior Detection.

Yan Tong, Jian Zhang, Wei Chen, Mingdi Xu, Tao Qin

Proceedings of the Communications and Networking, 2017

Generalization Error Bounds for Optimization Algorithms via Stability.

Qi Meng, Yue Wang, Wei Chen, Taifeng Wang, Zhiming Ma, Tie-Yan Liu

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Asynchronous Stochastic Proximal Optimization Algorithms with Variance Reduction.

Qi Meng, Wei Chen, Jingcheng Yu, Taifeng Wang, Zhiming Ma, Tie-Yan Liu

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Asynchronous Stochastic Gradient Descent with Delay Compensation for Distributed Deep Learning.

Shuxin Zheng, Qi Meng, Taifeng Wang, Wei Chen, Nenghai Yu, Zhiming Ma, Tie-Yan Liu

CoRR, 2016

A Communication-Efficient Parallel Algorithm for Decision Tree.

Qi Meng, Guolin Ke, Taifeng Wang, Wei Chen, Qiwei Ye, Zhiming Ma, Tie-Yan Liu

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Asynchronous Accelerated Stochastic Gradient Descent.

Qi Meng, Wei Chen, Jingcheng Yu, Taifeng Wang, Zhiming Ma, Tie-Yan Liu

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

On the Depth of Deep Neural Networks: A Theoretical View.

Shizhao Sun, Wei Chen, Liwei Wang, Xiaoguang Liu, Tie-Yan Liu

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Large Margin Deep Neural Networks: Theory and Algorithms.

Shizhao Sun, Wei Chen, Liwei Wang, Tie-Yan Liu

CoRR, 2015

Mechanism Learning with Mechanism Induced Data.

Tie-Yan Liu, Wei Chen, Tao Qin

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Generalization Analysis for Game-Theoretic Machine Learning.

Haifang Li, Fei Tian, Wei Chen, Tao Qin, Zhiming Ma, Tie-Yan Liu

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Sponsored Search Auctions: Recent Advances and Future Directions.

Tao Qin, Wei Chen, Tie-Yan Liu

ACM Trans. Intell. Syst. Technol., 2014

Generalization Analysis for Game-Theoretic Machine Learning.

Haifang Li, Fei Tian, Wei Chen, Tao Qin, Tie-Yan Liu

CoRR, 2014

Sampling dilemma: towards effective data sampling for click prediction in sponsored search.

Jun Feng, Jiang Bian, Taifeng Wang, Wei Chen, Xiaoyan Zhu, Tie-Yan Liu

Proceedings of the Seventh ACM International Conference on Web Search and Data Mining, 2014

Generalized second price auction with probabilistic broad match.

Wei Chen, Di He, Tie-Yan Liu, Tao Qin, Yixin Tao, Liwei Wang

Proceedings of the ACM Conference on Economics and Computation, 2014

Agent Behavior Prediction and Its Generalization Analysis.

Fei Tian, Haifang Li, Wei Chen, Tao Qin, Enhong Chen, Tie-Yan Liu

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013

Online learning for auction mechanism in bandit setting.

Di He, Wei Chen, Liwei Wang, Tie-Yan Liu

Decis. Support Syst., 2013

A Theoretical Analysis of NDCG Type Ranking Measures

Yining Wang, Liwei Wang, Yuanzhi Li, Di He, Tie-Yan Liu, Wei Chen

CoRR, 2013

A Game-Theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search.

Di He, Wei Chen, Liwei Wang, Tie-Yan Liu

Proceedings of the IJCAI 2013, 2013

2012

Convergence Analysis for Weighted Joint Strategy Fictitious Play in Generalized Second Price Auction.

Lei Yao, Wei Chen, Tie-Yan Liu

Proceedings of the Internet and Network Economics - 8th International Workshop, 2012

2010

Two-Layer Generalization Analysis for Ranking Using Rademacher Average.

Wei Chen, Tie-Yan Liu, Zhiming Ma

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009

Ranking Measures and Loss Functions in Learning to Rank.

Wei Chen, Tie-Yan Liu, Yanyan Lan, Zhiming Ma, Hang Li

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009