Bai, Yu

58 publications

NeurIPS 2025 Accelerated Vertical Federated Adversarial Learning Through Decoupling Layer-Wise Dependencies Tianxing Man, Yu Bai, Ganyu Wang, Jinjie Fang, Haoran Fang, Bin Gu, Yi Chang

AAAI 2025 Excluding the Impossible for Open Vocabulary Semantic Segmentation Shiyuan Zhao, Baodi Liu, Yu Bai, Weifeng Liu, Shuai Shao

AAAI 2025 Text2Data: Low-Resource Data Generation with Textual Control Shiyu Wang, Yihao Feng, Tian Lan, Ning Yu, Yu Bai, Ran Xu, Huan Wang, Caiming Xiong, Silvio Savarese

CVPR 2025 TopV: Compatible Token Pruning with Inference Time Optimization for Fast and Low-Memory Multimodal Vision Language Model Cheng Yang, Yang Sui, Jinqi Xiao, Lingyi Huang, Yu Gong, Chendi Li, Jinghua Yan, Yu Bai, Ponnuswamy Sadayappan, Xia Hu, Bo Yuan

NeurIPS 2025 Transcending Cost-Quality Tradeoff in Agent Serving via Session-Awareness Yanyu Ren, Li Chen, Dan Li, Xizheng Wang, Zhiyuan Wu, Yukai Miao, Yu Bai

NeurIPSW 2024 Active-Dormant Attention Heads: Mechanistically Demystifying Extreme-Token Phenomena in LLMs Tianyu Guo, Druv Pai, Yu Bai, Jiantao Jiao, Michael Jordan, Song Mei

AAAI 2024 Collaborative Consortium of Foundation Models for Open-World Few-Shot Learning Shuai Shao, Yu Bai, Yan Wang, Baodi Liu, Bin Liu

CVPR 2024 DeIL: Direct-and-Inverse CLIP for Open-World Few-Shot Learning Shuai Shao, Yu Bai, Yan Wang, Baodi Liu, Yicong Zhou

ICLR 2024 How Do Transformers Learn In-Context Beyond Simple Functions? a Case Study on Learning with Representations Tianyu Guo, Wei Hu, Song Mei, Huan Wang, Caiming Xiong, Silvio Savarese, Yu Bai

ICML 2024 Is Inverse Reinforcement Learning Harder than Standard Reinforcement Learning? a Theoretical Perspective Lei Zhao, Mengdi Wang, Yu Bai

ECCV 2024 Norma: A Noise Robust Memory-Augmented Framework for Whole Slide Image Classification Yu Bai, Bo Zhang, Zheng Zhang, Shuo Yan, Zibo Ma, Wu Liu, Xiuzhuang Zhou, Xiangyang Gong, Wendong Wang

ICLR 2024 Sample-Efficient Learning of POMDPs with Multiple Observations in Hindsight Jiacheng Guo, Minshuo Chen, Huan Wang, Caiming Xiong, Mengdi Wang, Yu Bai

ICLRW 2024 Text2Data: Low-Resource Data Generation with Textual Control Shiyu Wang, Yihao Feng, Tian Lan, Ning Yu, Yu Bai, Ran Xu, Huan Wang, Caiming Xiong, Silvio Savarese

ICLR 2024 Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining Licong Lin, Yu Bai, Song Mei

COLT 2023 Breaking the Curse of Multiagency: Provably Efficient Decentralized Multi-Agent RL with Function Approximation Yuanhao Wang, Qinghua Liu, Yu Bai, Chi Jin

NeurIPS 2023 Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations Minshuo Chen, Yu Bai, H. Vincent Poor, Mengdi Wang

ICMLW 2023 Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations Minshuo Chen, Yu Bai, H. Vincent Poor, Mengdi Wang

NeurIPSW 2023 How Do Transformers Learn In-Context Beyond Simple Functions? a Case Study on Learning with Representations Tianyu Guo, Wei Hu, Song Mei, Huan Wang, Caiming Xiong, Silvio Savarese, Yu Bai

ICML 2023 Improved Online Conformal Prediction via Strongly Adaptive Online Learning Aadyot Bhatnagar, Huan Wang, Caiming Xiong, Yu Bai

ICLR 2023 Learning Rationalizable Equilibria in Multiplayer Games Yuanhao Wang, Dingwen Kong, Yu Bai, Chi Jin

ICML 2023 Lower Bounds for Learning in Revealing POMDPs Fan Chen, Huan Wang, Caiming Xiong, Song Mei, Yu Bai

ICML 2023 Offline Learning in Markov Games with General Function Approximation Yuheng Zhang, Yu Bai, Nan Jiang

ICLR 2023 Partially Observable RL with B-Stability: Unified Structural Condition and Sharp Sample-Efficient Algorithms Fan Chen, Yu Bai, Song Mei

ICMLW 2023 Sample-Efficient Learning of POMDPs with Multiple Observations in Hindsight Jiacheng Guo, Minshuo Chen, Huan Wang, Caiming Xiong, Mengdi Wang, Yu Bai

ICLR 2023 The Role of Coverage in Online Reinforcement Learning Tengyang Xie, Dylan J Foster, Yu Bai, Nan Jiang, Sham M. Kakade

NeurIPSW 2023 Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining Licong Lin, Yu Bai, Song Mei

NeurIPSW 2023 Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining Licong Lin, Yu Bai, Song Mei

NeurIPS 2023 Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection Yu Bai, Fan Chen, Huan Wang, Caiming Xiong, Song Mei

ICMLW 2023 Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection Yu Bai, Fan Chen, Huan Wang, Caiming Xiong, Song Mei

NeurIPS 2023 What Can a Single Attention Layer Learn? a Study Through the Random Features Lens Hengyu Fu, Tianyu Guo, Yu Bai, Song Mei

NeurIPS 2022 Efficient Phi-Regret Minimization in Extensive-Form Games via Online Mirror Descent Yu Bai, Chi Jin, Song Mei, Ziang Song, Tiancheng Yu

ICLR 2022 Efficient and Differentiable Conformal Prediction with General Function Classes Yu Bai, Song Mei, Huan Wang, Yingbo Zhou, Caiming Xiong

NeurIPS 2022 Identifying Good Directions to Escape the NTK Regime and Efficiently Learn Low-Degree Plus Sparse Polynomials Eshaan Nichani, Yu Bai, Jason Lee

UAI 2022 Local Calibration: Metrics and Recalibration Rachel Luo, Aadyot Bhatnagar, Yu Bai, Shengjia Zhao, Huan Wang, Caiming Xiong, Silvio Savarese, Stefano Ermon, Edward Schmerling, Marco Pavone

ICML 2022 Near-Optimal Learning of Extensive-Form Games with Imperfect Information Yu Bai, Chi Jin, Song Mei, Tiancheng Yu

ICLRW 2022 Near-Optimal Learning of Extensive-Form Games with Imperfect Information Yu Bai, Chi Jin, Song Mei, Tiancheng Yu

NeurIPS 2022 Policy Optimization for Markov Games: Unified Framework and Faster Convergence Runyu Zhang, Qinghua Liu, Huan Wang, Caiming Xiong, Na Li, Yu Bai

NeurIPS 2022 Sample-Efficient Learning of Correlated Equilibria in Extensive-Form Games Ziang Song, Song Mei, Yu Bai

IJCAI 2022 Stage-Wise Stylistic Headline Generation: Style Generation and Summarized Content Insertion Jiaao Zhan, Yang Gao, Yu Bai, Qianhui Liu

ICLR 2022 When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently? Ziang Song, Song Mei, Yu Bai

AISTATS 2021 Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning Ming Yin, Yu Bai, Yu-Xiang Wang

ICML 2021 A Sharp Analysis of Model-Based Reinforcement Learning with Self-Play Qinghua Liu, Tiancheng Yu, Yu Bai, Chi Jin

ICML 2021 Don’t Just Blame Over-Parametrization for Over-Confidence: Theoretical Analysis of Calibration in Binary Classification Yu Bai, Song Mei, Huan Wang, Caiming Xiong

ICML 2021 Exact Gap Between Generalization Error and Uniform Convergence in Random Feature Models Zitong Yang, Yu Bai, Song Mei

AAAI 2021 Exploring Explainable Selection to Control Abstractive Summarization Haonan Wang, Yang Gao, Yu Bai, Mirella Lapata, Heyan Huang

ICML 2021 How Important Is the Train-Validation Split in Meta-Learning? Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, Jason Lee, Sham Kakade, Huan Wang, Caiming Xiong

NeurIPS 2021 Near-Optimal Offline Reinforcement Learning via Double Variance Reduction Ming Yin, Yu Bai, Yu-Xiang Wang

NeurIPS 2021 Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning Tengyang Xie, Nan Jiang, Huan Wang, Caiming Xiong, Yu Bai

NeurIPS 2021 Sample-Efficient Learning of Stackelberg Equilibria in General-Sum Games Yu Bai, Chi Jin, Huan Wang, Caiming Xiong

NeurIPS 2021 Understanding the Under-Coverage Bias in Uncertainty Estimation Yu Bai, Song Mei, Huan Wang, Caiming Xiong

ICLR 2020 Beyond Linearization: On Quadratic and Higher-Order Approximation of Wide Neural Networks Yu Bai, Jason D. Lee

NeurIPS 2020 Near-Optimal Reinforcement Learning with Self-Play Yu Bai, Chi Jin, Tiancheng Yu

ICML 2020 Provable Self-Play Algorithms for Competitive Reinforcement Learning Yu Bai, Chi Jin

NeurIPS 2020 Towards Understanding Hierarchical Learning: Benefits of Neural Representations Minshuo Chen, Yu Bai, Jason Lee, Tuo Zhao, Huan Wang, Caiming Xiong, Richard Socher

ICLR 2019 Approximability of Discriminators Implies Diversity in GANs Yu Bai, Tengyu Ma, Andrej Risteski

NeurIPS 2019 Provably Efficient Q-Learning with Low Switching Cost Yu Bai, Tengyang Xie, Nan Jiang, Yu-Xiang Wang

ICLR 2019 ProxQuant: Quantized Neural Networks via Proximal Operators Yu Bai, Yu-Xiang Wang, Edo Liberty

ICLR 2019 Subgradient Descent Learns Orthogonal Dictionaries Yu Bai, Qijia Jiang, Ju Sun