Wang, Che

10 publications

NeurIPS 2025 AegisGuard: RL-Guided Adapter Tuning for TEE-Based Efficient & Secure On-Device Inference Che Wang, Ziqi Zhang, Yinggui Wang, Tiantong Wang, Yurong Hao, Jianbo Gao, Tao Wei, Yang Cao, Zhong Chen, Wei Yang Bryan Lim

ICLR 2024 Pre-Training with Synthetic Data Helps Offline Reinforcement Learning Zecheng Wang, Che Wang, Zixuan Dong, Keith W. Ross

NeurIPSW 2022 Aggressive Q-Learning with Ensembles: Achieving Both High Sample Efficiency and High Asymptotic Performance Yanqiu Wu, Xinyue Chen, Che Wang, Yiming Zhang, Keith W. Ross

ICLR 2022 On the Convergence of the Monte Carlo Exploring Starts Algorithm for Reinforcement Learning Che Wang, Shuhan Yuan, Kai Shao, Keith W. Ross

NeurIPS 2022 Reinforcement Learning with Automated Auxiliary Loss Search Tairan He, Yuge Zhang, Kan Ren, Minghuan Liu, Che Wang, Weinan Zhang, Yuqing Yang, Dongsheng Li

NeurIPS 2022 VRL3: A Data-Driven Framework for Visual Deep Reinforcement Learning Che Wang, Xufang Luo, Keith Ross, Dongsheng Li

NeurIPSW 2021 Functional Response Conditional Variational Auto-Encoders for Inverse Design of Metamaterials Che Wang, Yuhao Fu, Ke Deng, Chunlin Ji

ICLR 2021 Randomized Ensembled Double Q-Learning: Learning Fast Without a Model Xinyue Chen, Che Wang, Zijian Zhou, Keith W. Ross

NeurIPS 2020 BAIL: Best-Action Imitation Learning for Batch Deep Reinforcement Learning Xinyue Chen, Zijian Zhou, Zheng Wang, Che Wang, Yanqiu Wu, Keith Ross

ICML 2020 Striving for Simplicity and Performance in Off-Policy DRL: Output Normalization and Non-Uniform Sampling Che Wang, Yanqiu Wu, Quan Vuong, Keith Ross