Jinglin Chen - RankMe

24 papers A* 7A 1Misc 1Journal 13Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	HierarchicalKV: A GPU Hash Table with Cache Semantics for Continuous Online Embedding Storage. CoRR Haidong Rong, Jiashu Yao, Matthias Langer, Shijie Liu, Li Fan, Dongxin Wang, Jia He, Jinglin Chen, Jiaheng Rang, Julian Qian, Mengyao Xu, Fan Yu, Minseok Lee, Zehuan Wang, Even Oldridge
2025	A*	`conf`	Faster In-Context Learning for LLMs via N-Gram Trie Speculative Decoding. EMNLP Jinglin Chen, Qiwei Li, Zuchao Li, Baoyuan Qi, Guoming Liu, Haojun Ai, Hai Zhao, Ping Wang
2024	J	`jnl`	Model-Free Representation Learning and Exploration in Low-Rank MDPs. J. Mach. Learn. Res. Aditya Modi, Jinglin Chen, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal
2023	Misc	`conf`	Extended Abstract: Learning in Low-rank MDPs with Density Features. CISS Audrey Huang, Jinglin Chen, Nan Jiang
2023	J	`jnl`	Reinforcement Learning in Low-Rank MDPs with Density Features. CoRR Audrey Huang, Jinglin Chen, Nan Jiang
2023	A*	`conf`	Reinforcement Learning in Low-rank MDPs with Density Features. ICML Audrey Huang, Jinglin Chen, Nan Jiang
2022	J	`jnl`	Nonstationary Reinforcement Learning with Linear Function Approximation. Trans. Mach. Learn. Res. Huozhi Zhou, Jinglin Chen, Lav R. Varshney, Ashish Jagmohan
2022	J	`jnl`	Offline Reinforcement Learning Under Value and Density-Ratio Realizability: the Power of Gaps. CoRR Jinglin Chen, Nan Jiang
2022	A	`conf`	Offline reinforcement learning under value and density-ratio realizability: The power of gaps. UAI Jinglin Chen, Nan Jiang
2022	A*	`conf`	On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL. NeurIPS Jinglin Chen, Aditya Modi, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal
2022	J	`jnl`	On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL. CoRR Jinglin Chen, Aditya Modi, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal
2022	A*	`conf`	Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality. ICLR Jiawei Huang, Jinglin Chen, Li Zhao, Tao Qin, Nan Jiang, Tie-Yan Liu
2022	J	`jnl`	Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality. CoRR Jiawei Huang, Jinglin Chen, Li Zhao, Tao Qin, Nan Jiang, Tie-Yan Liu
2021	A*	`conf`	Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration. AAAI Priyank Agrawal, Jinglin Chen, Nan Jiang
2021	J	`jnl`	Model-free Representation Learning and Exploration in Low-rank MDPs. CoRR Aditya Modi, Jinglin Chen, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal
2020	J	`jnl`	Accelerating Nonconvex Learning via Replica Exchange Langevin Diffusion. CoRR Yi Chen, Jinglin Chen, Jing Dong, Jian Peng, Zhaoran Wang
2020	J	`jnl`	Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration. CoRR Priyank Agrawal, Jinglin Chen, Nan Jiang
2020	J	`jnl`	Nonstationary Reinforcement Learning with Linear Function Approximation. CoRR Huozhi Zhou, Jinglin Chen, Lav R. Varshney, Ashish Jagmohan
2019	—	`conf`	Accelerating Nonconvex Learning via Replica Exchange Langevin diffusion. ICLR (Poster) Yi Chen, Jinglin Chen, Jing Dong, Jian Peng, Zhaoran Wang
2019	A*	`conf`	Information-Theoretic Considerations in Batch Reinforcement Learning. ICML Jinglin Chen, Nan Jiang
2019	J	`jnl`	Information-Theoretic Considerations in Batch Reinforcement Learning. CoRR Jinglin Chen, Nan Jiang
2018	A*	`conf`	Efficient Localized Inference for Large Graphical Models. IJCAI Jinglin Chen, Jian Peng, Qiang Liu
2017	J	`jnl`	Efficient Localized Inference for Large Graphical Models. CoRR Jinglin Chen, Jian Peng, Qiang Liu
2008	—	`conf`	DTAD: A Dynamic Taint Analysis Detector for Information Security. WAIM Zhiwen Bai, Liming Wang, Jinglin Chen, Lin Xu, Jian Liu, Xiyang Liu