Wang, Yafei

6 publications

ICML 2025 Differentially Private Analysis for Binary Response Models: Optimality, Estimation, and Inference Ce Zhang, Yixin Han, Yafei Wang, Xiaodong Yan, Linglong Kong, Ting Li, Bei Jiang

NeurIPS 2025 Intrinsic Benefits of Categorical Distributional Loss: Uncertainty-Aware Regularized Exploration in Reinforcement Learning Ke Sun, Yingnan Zhao, Enze Shi, Yafei Wang, Xiaodong Yan, Bei Jiang, Linglong Kong

ICCV 2025 V2XScenes: A Multiple Challenging Traffic Conditions Dataset for Large-Range Vehicle-Infrastructure Collaborative Perception Bowen Wang, Yafei Wang, Wei Gong, Siheng Chen, Genjia Liu, Minhao Xiong, Chin Long Ng

ICML 2024 Sample Average Approximation for Conditional Stochastic Optimization with Dependent Data Yafei Wang, Bo Pan, Mei Li, Jianya Lu, Lingchen Kong, Bei Jiang, Linglong Kong

AAAI 2022 Sample Average Approximation for Stochastic Optimization with Dependent Data: Performance Guarantees and Tractability Yafei Wang, Bo Pan, Wei Tu, Peng Liu, Bei Jiang, Chao Gao, Wei Lu, Shangling Jui, Linglong Kong

NeurIPS 2021 Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization Ke Sun, Yafei Wang, Yi Liu, Yingnan Zhao, Bo Pan, Shangling Jui, Bei Jiang, Linglong Kong