Publications

See the full publication list at Google Scholar.

Authored Book

Songyang Zhang (Ed.), Shuai Zhang (Ed.), Chuan Huang (Ed.). “Generative Learning for Wireless Communications: Fundamentals and Applications.” Elsevier Science Publishing Co. Inc., 2026.

Conference Papers

Top ML/AI Conferences

Hongkang Li, Yihua Zhang, Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen. “When Is Task Vector Provably Effective for Model Editing? A Generalization Analysis of Nonlinear Transformers.” International Conference on Learning Representations (ICLR, Oral), 2025.
Nowaz Chowdhury, Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen. “Patch-Level Routing in Mixture-of-Experts Is Provably Sample-Efficient for Convolutional Neural Networks.” International Conference on Machine Learning (ICML, Oral), 2023.
Haixu Liao, Yating Zhou, Songyang Zhang, Meng Wang, Shuai Zhang. “Theoretical Analysis of Contrastive Learning under Imbalanced Data: From Training Dynamics to a Pruning Solution.” International Conference on Learning Representations (ICLR), 2026.
Mugunthan Shandirasegaran, Hongkang Li, Songyang Zhang, Meng Wang, Shuai Zhang. “A Theoretical Analysis of Mamba’s Training Dynamics: Filtering Relevant Features for Generalization in State Space Models.” International Conference on Learning Representations (ICLR), 2026.
Jiawei Sun, Shuai Zhang, Hongkang Li, Meng Wang. “Contrastive Learning with Data Misalignment: Feature Purity, Training Dynamics, and Theoretical Generalization Guarantees.” Advances in Neural Information Processing Systems (NeurIPS), 2025.
Zixi Wang, Yushe Cao, Yubo Huang, Jinzhu Wei, Jingzehua Xu, Shuai Zhang, Xin Lai. “Self-Training with Dynamic Weighting for Robust Gradual Domain Adaptation.” Advances in Neural Information Processing Systems (NeurIPS), 2025.
Shuai Zhang, Heshan Devaka Fernando, Miao Liu, Keerthiram Murugesan, Songtao Lu, Pin-Yu Chen, Tianyi Chen, Meng Wang. “SF-DQN: Provable Knowledge Transfer Using Successor Features for Deep Reinforcement Learning.” International Conference on Machine Learning (ICML), 2024.
Shusen Jing, Anlan Yu, Shuai Zhang, Songyang Zhang. “FedSC: Provable Federated Self-Supervised Learning with Spectral Contrastive Objective over Non-IID Data.” International Conference on Machine Learning (ICML), 2024.
Shuai Zhang, Hongkang Li, Meng Wang, Miao Liu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Keerthiram Murugesan, Subhajit Chaudhury. “On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration.” Advances in Neural Information Processing Systems (NeurIPS), 2023.
Shuai Zhang, Meng Wang, Pin-Yu Chen, Sijia Liu, Songtao Lu, Miao Liu. “Joint Edge–Model Sparse Learning Is Provably Efficient for Graph Neural Networks.” International Conference on Learning Representations (ICLR), 2023.
Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong. “How Unlabeled Data Improve Generalization in Self-Training? A One-Hidden-Layer Theoretical Analysis.” International Conference on Learning Representations (ICLR), 2022.
Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong. “Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Sparse Neural Networks.” Advances in Neural Information Processing Systems (NeurIPS), vol. 34, pp. 2707–2720, 2021.
Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong. “Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-Hidden-Layer Case.” International Conference on Machine Learning (ICML), pp. 11268–11277, 2020.

Selective AI and Applied AI Conferences

Yihua Zhang, Hongkang Li, Yuguang Yao, Aochuan Chen, Shuai Zhang, Pin-Yu Chen, Meng Wang, Sijia Liu. “Visual Prompting Reimagined: The Power of Activation Prompts.” International Conference on Artificial Intelligence and Statistics (AISTATS), 2026.
Zixi Wang, Yubo Huang, Jingzehua Xu, Jinzhu Wei, Shuai Zhang, Xin Lai. “Multi-Modal Gradual Domain Osmosis: Stepwise Dynamic Learning with Batch Matching for Gradual Domain Adaptation.” ACM International Conference on Multimedia (ACMMM), 2025.
Yimian Ding, Jingzehua Xu, Guanwen Xie, Shuai Zhang, Yi Li. “Make Your AUV Adaptive: An Environment-Aware Reinforcement Learning Framework for Underwater Tasks.” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025.
Guanwen Xie, Jingzehua Xu, Yimian Ding, Zhi Zhang, Shuai Zhang, Yi Li. “Never Too Prim to Swim: An LLM-Enhanced RL-Based Adaptive Sea-Surface Controller for AUVs under Extreme Sea Conditions.” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025.

Signal Processing and Communications Conferences

Song Gao, Songyang Zhang, Shusen Jing, Shuai Zhang, Xiangwei Zhou, Yue Wang, Zhipeng Cai. “Towards Efficient Federated Learning of Networked Mixture-of-Experts for Mobile Edge Computing.” IEEE Vehicular Technology Conference (VTC), 2026.
Yubo Huang, Xin Lai, Muyang Ye, Anran Zhu, Zixi Wang, Jingzehua Xu, Shuai Zhang, Zhiyuan Zhou, Weijie Niu. “LHQ-SVC: Lightweight and High-Quality Singing Voice Conversion Modeling.” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025.
Jingzehua Xu, Guanwen Xie, Xinqi Wang, Yimian Ding, Shuai Zhang. “USV–AUV Collaboration Framework for Underwater Tasks under Extreme Sea Conditions.” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025.
Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong. “Guaranteed Convergence of Training Convolutional Neural Networks via Accelerated Gradient Descent.” Conference on Information Sciences and Systems (CISS), pp. 1–6, 2020.
Hongkang Li, Shuai Zhang, Meng Wang. “Learning and Generalization of One-Hidden-Layer Neural Networks, Going Beyond Standard Gaussian Data.” Conference on Information Sciences and Systems (CISS), pp. 37–42, 2022.
Meng Wang, Joe H. Chow, Yingshuai Hao, Shuai Zhang, Wenting Li, Ren Wang, Pengzhi Gao, Christopher Lackner, Evangelos Farantatos, Mahendra Patel. “A Low-Rank Framework of PMU Data Recovery and Event Identification.” IEEE International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA), pp. 1–9, 2019.
Shuai Zhang, Meng Wang. “Correction of Simultaneous Bad Measurements by Exploiting the Low-Rank Hankel Structure.” IEEE International Symposium on Information Theory (ISIT), pp. 646–650, 2018.

Journal Articles

Yating Zhou, Shuai Zhang, Meng Wang. “Mid-Term Load Forecasting with Minimal Data: An In-Context-Learning-Aware Approach Using Large Language Models.” IEEE Transactions on Power Systems, 2026.
Jingzehua Xu, Guanwen Xie, Jiwei Tang, Yimian Ding, Weiyi Liu, Junhao Huang, Shuai Zhang, Yi Li. “Never Too Cocky to Cooperate: A Fisher-Information-Matrix- and RL-Based USV–AUV Collaborative System for Underwater Tasks in Extreme Sea Conditions.” IEEE Transactions on Mobile Computing, 2026.
Xiaobing Chen, Boyang Zhang, Xiangwei Zhou, Mingxuan Sun, Shuai Zhang, Songyang Zhang, Geoffrey Ye Li. “Efficient Training of Large-Scale AI Models Through Federated Mixture-of-Experts: A System-Level Approach.” IEEE Communications Magazine, 2025.
Hongkang Li, Shuai Zhang, Yihua Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen. “How Does Promoting the Minority Fraction Affect Generalization? A Theoretical Study of One-Hidden-Layer Neural Networks on Group Imbalance.” IEEE Journal of Selected Topics in Signal Processing, vol. 18, no. 2, pp. 216–231, 2024.
Jingzehua Xu, Guanwen Xie, Zekai Zhang, Xiangwang Hou, Shuai Zhang, Yong Ren, Dusit Niyato. “UPEGSim: An RL-Enabled Simulator for Unmanned Underwater Vehicles Dedicated to the Underwater Pursuit–Evasion Game.” IEEE Internet of Things Journal, vol. 12, no. 3, pp. 2334–2346, 2025.
Guanwen Xie, Jingzehua Xu, Ziqi Zhang, Xiangwang Hou, Dongfang Ma, Shuai Zhang, Yong Ren, Dusit Niyato. “Is Fisher All You Need in the Multi-AUV Underwater Target Tracking Task?” IEEE Transactions on Mobile Computing, 2025.
Shuai Zhang, Meng Wang. “Correction of Corrupted Columns through Fast Robust Hankel Matrix Completion.” IEEE Transactions on Signal Processing, vol. 67, no. 10, pp. 2580–2594, 2019.
Shuai Zhang, Meng Wang, Jinjun Xiong, Sijia Liu, Pin-Yu Chen. “Improved Linear Convergence of Training CNNs with Generalizability Guarantees: A One-Hidden-Layer Case.” IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 6, pp. 2622–2635, 2020.
Shuai Zhang, Yingshuai Hao, Meng Wang, Joe H. Chow. “Multichannel Hankel Matrix Completion through Nonconvex Optimization.” IEEE Journal of Selected Topics in Signal Processing, vol. 12, no. 4, pp. 617–632, 2018.