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个人简介

I am a professor at School of Computer Science and Technology and School of Mathematical Science , East China Normal University. Before that, I received my Bachelor degree and PhD degree from Nanjing University in 2009 and 2014 respectively under the supervision of Professor Bingsheng He. During my PhD study, I was supported by the National Scholarship Council for joint PhD at the University of Minnesota under the supervision of Professor Zhi-Quan Luo. Awards 2022, Nomination Award for Youth Science and Technology Award of Operational Research Society of China 2022, Shanghai QiMingXing 2021, IEEE Signal Processing Society Best Paper Award

研究领域

Foundation Model for Operations Research Learn to Optimize: continuous or distributed cases Distributed Optimization Multi-agent Learning and AI Agent

近期论文

查看导师新发文章 (温馨提示:请注意重名现象,建议点开原文通过作者单位确认)

Generalized Variational Framework with Minimax Optimization for Parametric Blind Deconvolution Qichao Cao, Deren Han, Xiangfeng Wang, and Wenxing Zhang Inverse Problems 2024 Joint Design of Long-term Base Station Activation and Short-term Beamforming for Green Wireless Networks Jingran Lin, Mengyuan Ma, and Xiangfeng Wang IEEE Transactions on Wireless Communications 2024 Machine learning-driven multi-agent pathfinding: An overview《机器学习驱动的多智能体路径搜寻算法综述》 Xiangfeng Wang, and Wenhao Li Operations Research Transactions 运筹学学报 2023 F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning Wenhao Li, Bo Jin, Xiangfeng Wang, Junchi Yan, and Hongyuan Zha Journal of Machine Learning Research 2023 An Alternating Structure-adapted Bregman Proximal Gradient Descent Algorithm for Constrained Nonconvex Bonsmooth Optimization Problems and its Inertial Variant Xue Gao, Xiangju Cai, Xiangfeng Wang, and Deren Han Journal of Global Optimization 2023 Interactive Medical Image Segmentation with Self-Adaptive Confidence Calibration Wenhao Li, Chuyun Shen, Qisen Xu, Bin Hu, Bo Jin, Fengping Zhu, Yuxin Li, and Xiangfeng Wang Frontiers of Information Technology & Electronic Engineering (also published at 2022 NeurIPS Workshop on Human in the Loop Learning) 2023 Open-Set Signal Recognition Based on Transformer and Wasserstein Distance Wei Zhang, Da Huang, Minghui Zhou, Jingran Lin, and Xiangfeng Wang Applied Sciences 2023 Group Sparse Space Information Network with Joint Virtual Network Function Deployment and Maximum Flow Routing Strategy Huiting Yang, Wei Liu, Xiangfeng Wang, and Jiandong Li IEEE Transactions on Wireless Communications 2022 Multi Agent Deep Reinforcement Learning-based Urban Traffic Signal Management《面向城市交通信号优化的多智能体强化学习综述》 Yun Hua, Xiangfeng Wang, and Bo Jin Operations Research Transactions 运筹学学报 2022 Mitigating Disparate Impact on Model Accuracy in Differentially Private Learning Wenyan Liu, Xiangfeng Wang, Haikun Zheng, Bo Jin, Xiaoling Wang, and Hongyuan Zha Information Sciences 2022 Learning Structured Communication for Multi-agent Reinforcement Learning Junjie Sheng, Xiangfeng Wang, Bo Jin, Wenhao Li, Junchi Yan, Tsung-Hui Chang, Jun Wang, and Hongyuan Zha Autonomous Agents and Multi-Agent Systems 2022 Structured Cooperative Reinforcement Learning with Time-varying Composite Action Space Wenhao Li, Xiangfeng Wang, Bo Jin, Dijun Luo, and Hongyuan Zha IEEE Transactions on Pattern Analysis and Machine Intelligence 2022 Perturbation Techniques for Convergence Analysis of Proximal Gradient Method and Other First-order Algorithms via Variational Analysis Xiangfeng Wang, Jane J. Ye, Xiaoming Yuan, Shangzhi Zeng, and Jin Zhang Set-Valued and Variational Analysis 2022 Learning to Schedule Multi-NUMA Virtual Machines via Reinforcement Learning Junjie Sheng, Yiqiu Hu, Wenli Zhou, Lei Zhu, Bo Jin, Jun Wang, and Xiangfeng Wang Pattern Recognition 2022 The O(1/n) Worst-case Convergence Rate of ADMM with Variable Penalty Parameters 《变惩罚参数交替方向法的O(1/n)迭代复杂度分析》 Xingju Cai, Xiangfeng Wang, and Wenxing Zhang Numerical Mathematics A Journal of Chinese Universities 高等学校计算数学学报 2021 | Commemorate the 100th anniversary of the birth of Professor Xuchu He Boundary-aware Supervoxel-level Iteratively Refined Interactive 3D Image Segmentation with Multi-agent Reinforcement Learning Chaofan Ma, Qisen Xu, Xiangfeng Wang, Bo Jin, Xiaoyu Zhang, Yanfeng Wang, and Ya Zhang IEEE Transactions on Medical Imaging 2021 Distributed and Parallel ADMM for Structured Nonconvex Optimization Problem Xiangfeng Wang, Junchi Yan, Bo Jin, and wenhao Li IEEE Transactions on Cybernetics 2021 Survey on Fairness in Trustworthy Machine Learning Wenyan Liu, Chuyun Shen, Xiangfeng Wang, Bo Jin, Xingjian Lu, Xiaoling Wang, Hongyuan Zha, and Jifeng He Journal of Software 2021 The Distance Between Convex Sets with Minkowski Sum Structure: Application to Collision Detection Xiangfeng Wang, Junping Zhang, and Wenxing Zhang Computational Optimization and Applications 2020 A Block Successive Upper Bound Minimization Method of Multipliers for Linearly Constrained Convex Optimization Mingyi Hong, Tsung-Hui Chang, Xiangfeng Wang, Meisam Razaviyayn, Shiqian Ma, and Zhi-Quan Luo Mathematics of Operations Research 2020 Joint Active Learning with Feature Selection via CUR Matrix Decomposition Changsheng Li, Xiangfeng Wang, Weishan Dong, Junchi Yan, Qingshan Liu, and Hongyuan Zha IEEE Transactions on Pattern Analysis and Machine Intelligence 2019 Dynamic Structure Embedded Online Multiple-Output Regression for Streaming Data Changsheng Li, Fan Wei, Weishan Dong, Xiangfeng Wang, Qingshan Liu, and Xin Zhang IEEE Transactions on Pattern Analysis and Machine Intelligence 2019 Implementing the ADMM to Big Datasets: A Case Study of LASSO Hangrui Yue, Qingzhi Yang, Xiangfeng Wang, and Xiaoming Yuan SIAM Journal on Scientific Computing 2018 On the Flexibility of Block Coordinate Descent for Large-Scale Optimization Xiangfeng Wang, Wenjie Zhang, Junchi Yan, Xiaoming Yuan, and Hongyuan Zha Neurocomputing 2018 Iteration Complexity Analysis of Block Coordinate Descent Methods Mingyi Hong, Xiangfeng Wang, Meisam Razaviyayn, and Zhi-Quan Luo Mathematical Programming 2017 Asynchronous Distributed ADMM for Large-Scale Optimization-Part I: Algorithm and Convergence Analysis Tsung-Hui Chang, Mingyi Hong, Wei-Cheng Liao, and Xiangfeng Wang IEEE Transactions on Signal Processing 2016 Asynchronous Distributed ADMM for Large-Scale Optimization-Part II: Linear Convergence Analysis and Numerical Performances Tsung-Hui Chang, Wei-Cheng Liao, Mingyi Hong, and Xiangfeng Wang IEEE Transactions on Signal Processing 2016 On the Convergence Rate of a Class of Proximal-Based Decomposition Methods for Monotone Variational Inequalities Xiangfeng Wang Journal of the Operations Research Society of China 2015 Solving Multiple-Block Separable Convex Minimization Problems using Two-Block ADMM Xiangfeng Wang, Mingyi Hong, Shiqian Ma, and Zhi-Quan Luo Pacific Journal of Optimization 2015 Multi-Agent Distributed Large-Scale Optimization by Inexact Consensus ADMM Tsung-Hui Chang, Mingyi Hong, and Xiangfeng Wang IEEE Transactions on Signal Processing 2015 | IEEE Signal Processing Society Best Paper Award Efficient InSAR Phase Noise Reduction via Total Variation Regularization Xiaomei Luo, Xiangfeng Wang, Zhiyong Suo, and Zhenfang Li Science China (Information Sciences) 2015 The Linearized Alternating Direction Method of Multipliers for Dantzig Selector Xiangfeng Wang, and Xiaoming Yuan SIAM Journal of Scientific Computing 2012 Conference Papers Long-tailed Diffusion Models with Oriented Calibration Tianjiao Zhang, Huangjie Zheng, Jiangchao Yao, Xiangfeng Wang, Mingyuan Zhou, Ya Zhang, and Yanfeng Wang ICLR 2024 Temporally-Extended Prompts Optimization for SAM in Interactive Medical Image Segmentation Chuyun Shen, Wenhao Li, Ya Zhang, Yanfeng Wang, and Xiangfeng Wang BIBM 2023 Hierarchical Diffusion for Offline Decision Making Wenhao Li, Xiangfeng Wang, Bo Jin, and Hongyuan Zha ICML 2023 Learning Cooperative Oversubscription for Cloud by Chance-Constrained MARL Junjie Sheng, Lu Wang, Fangkai Yang, Bo Qiao, Hang Dong, Xiangfeng Wang, Bo Jin, Jun Wang, Si Qin, Saravan Rajmohan, Qingwei Lin, and Dongmei Zhang WWW 2023 Learning Optimal "Pigovian Tax" in Sequential Social Dilemmas Yun Hua, Shang Gao, Wenhao Li, Bo Jin, Xiangfeng Wang, and Hongyuan Zha AAMAS 2023 Obtaining Dyadic Fairness by Optimal Transport Moyi Yang, Junjie Sheng, Wenyan Liu, Bo Jin, Xiaoling Wang, and Xiangfeng Wang IEEE Big Data 2022 ReAssigner: A Plug-and-Play Virtual Machine Scheduling Intensifier for Heterogeneous Requests Haochuan Cui, Junjie Sheng, Bo Jin, Yiqiu Hu, Li Su, Lei Zhu, Wenli Zhou, and Xiangfeng Wang IEEE Big Data 2022 CLD-Net: Complement Local Detail For Medical Small-Object Segmentation Rui Chen, Xiangfeng Wang, Bo Jin, Jiaqi Tu, Fengping Zhu, and Yuxin Li BIBM 2022 VMAgent: A Practical Virtual Machine Scheduling Platform Junjie Sheng, Shengliang Cai, Haochuan Cui, Wenhao Li, Yun Hua, Bo Jin, Wenli Zhou, Yiqiu Hu, Lei Zhu, Qian Peng, Hongyuan Zha, and Xiangfeng Wang IJCAI 2022 | The VMAgent Simulator Multi-Agent Path Finding with Prioritized Communication Learning Wenhao Li, Hongjun Chen, Bo Jin, Wenzhe Tan, Hongyuan Zha, and Xiangfeng Wang ICRA 2022 Weighted Mean-Field Multi-Agent Reinforcement Learning via Reward Attribution Decomposition Tingyu Wu, Wenhao Li, Bo Jin, Wei Zhang, and Xiangfeng Wang DASFAA 2022 Dealing with Non-Stationarity in Multi-Agent Reinforcement Learning via Trust Region Decomposition Wenhao Li, Xiangfeng Wang, Bo Jin, Junjie Sheng, and Hongyuan Zha ICLR 2022 HMRL: Hyper-Meta Learning for Sparse Reward Reinforcement Learning Problem Yun Hua, Xiangfeng Wang, Bo Jin, Wenhao Li, Junchi Yan, Xiaofeng He, and Hongyuan Zha KDD 2021 Semi-supervised Medical Image Segmentation with Confidence Calibration Qisen Xu, Qian Wu, Yiqiu Hu, Bo Jin, Bin Hu, Fengping Zhu, Yuxin Li, and Xiangfeng Wang IJCNN 2021 Structured Diversification Emergence via Reinforced Organization Control and Hierarchical Consensus Learning Wenhao Li, Xiangfeng Wang, Bo Jin, Junjie Sheng, Yun Hua, and Hongyuan Zha AAMAS 2021 VSB$^2$-Net: Visual-Semantic Bi-Branch Network for Zero-Shot Hashing Xin Li, Xiangfeng Wang, Bo Jin, Wenjie Zhang, Junjie Wang, and Hongyuan Zha ICPR 2020 Heterogeneous Graph-based Knowledge Transfer for Generalized Zero-shot Learning Junjie Wang, Xiangfeng Wang, Bo Jin, Junchi Yan, Wenjie Zhang, and Hongyuan Zha ICPR 2020 Iteratively-Refined Interactive 3D Medical Image Segmentation with Multi-Agent Reinforcement Learning Xuan Liao, Wenhao Li, Qisen Xu, Xiangfeng Wang, Bo Jin, Xiaoyun Zhang, Ya Zhang, and Yanfeng Wang CVPR 2020 Visual-to-Semantic Hashing for Zero-shot Learning Xin Li, Xiaoyue Wen, Bo Jin, Xiangfeng Wang, Junjie Wang, and Jinghui Cai IJCNN 2020 A Fast Proximal Point Method for Computing Exact Wasserstein Distance Yujia Xie, Xiangfeng Wang, Ruijia Wang, and Hongyuan Zha UAI 2019 SparseMAAC: Sparse Attention for Multi-agent Reinforcement Learning Wenhao Li, Bo Jin, and Xiangfeng Wang DASFAA 2019 Deep eXtreme Multi-label Learning Wenjie Zhang, Junchi Yan, Xiangfeng Wang, and Hongyuan Zha ICMR 2018 Joint Day-Ahead Power Procurement and Load Scheduling using Stochastic ADMM Xiangfeng Wang, Mingyi Hong, Tsung-Hui Chang, Meisam Razaviyayn, and Zhi-Quan Luo ICASSP 2014

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