Lin Yang - RankMe

48 papers A* 30A 7B 1Journal 6Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	CryptoBench: A Dynamic Benchmark for Expert-Level Evaluation of LLM Agents in Cryptocurrency. CoRR Jiacheng Guo, Suozhi Huang, Zixin Yao, Yifan Zhang, Yifu Lu, Jiashuo Liu, Zihao Li, Nicholas Deng, Qixin Xiao, Jia Tian, Kanghong Zhan, Tianyi Li, Xiaochen Liu, Jason Ge, Chaoyang He, Kaixuan Huang, Lin Yang, Wenhao Huang, Mengdi Wang
2025	A*	`conf`	Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning. ICML Yiran Wang, Chenshu Liu, Yunfan Li, Sanae Amani, Bolei Zhou, Lin Yang
2025	J	`jnl`	I3S: Importance Sampling Subspace Selection for Low-Rank Optimization in LLM Pretraining. CoRR Haochen Zhang, Junze Yin, Guanchu Wang, Zirui Liu, Tianyi Zhang, Anshumali Shrivastava, Lin Yang, Vladimir Braverman
2025	A*	`conf`	Misspecified Q-Learning with Sparse Linear Function Approximation: Tight Bounds on Approximation Error. ICLR Ally Yalei Du, Lin Yang, Ruosong Wang
2025	A*	`conf`	Regret-Optimal List Replicable Bandit Learning: Matching Upper and Lower Bounds. ICLR Michael Chen, Aduri Pavan, N. V. Vinodchandran, Ruosong Wang, Lin Yang
2024	J	`jnl`	A collective AI via lifelong learning and sharing at the edge. Nat. Mac. Intell. Andrea Soltoggio, Eseoghene Ben-Iwhiwhu, Vladimir Braverman, Eric Eaton, Benjamin Epstein, Yunhao Ge, Lucy Halperin, Jonathan P. How, Laurent Itti, Michael A. Jacobs, Pavan Kantharaju, Long Le, Steven Lee, Xinran Liu, Sildomar T. Monteiro, David Musliner, Saptarshi Nath, Priyadarshini Panda, Christos Peridis, Hamed Pirsiavash, Vishwa S. Parekh, Kaushik Roy, Shahaf S. Shperberg, Hava T. Siegelmann, Peter Stone, Kyle Vedder, Jingfeng Wu, Lin Yang, Guangyao Zheng, Soheil Kolouri
2024	A*	`conf`	Confident Natural Policy Gradient for Local Planning in q NeurIPS Tian Tian, Lin Yang, Csaba Szepesvári
2024	A	`conf`	Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation. AISTATS Jiayi Huang, Han Zhong, Liwei Wang, Lin Yang
2024	A	`conf`	Multi-Agent Bandit Learning through Heterogeneous Action Erasure Channels. AISTATS Osama A. Hanna, Merve Karakas, Lin Yang, Christina Fragouli
2024	A*	`conf`	Uniform Last-Iterate Guarantee for Bandits and Reinforcement Learning. NeurIPS Junyan Liu, Yunfan Li, Ruosong Wang, Lin Yang
2023	A*	`conf`	Contexts can be Cheap: Solving Stochastic Contextual Bandits with Linear Bandit Algorithms. COLT Osama A. Hanna, Lin Yang, Christina Fragouli
2023	A*	`conf`	Distributed Contextual Linear Bandits with Minimax Optimal Communication Cost. ICML Sanae Amani, Tor Lattimore, András György, Lin Yang
2023	A*	`conf`	Does Sparsity Help in Learning Misspecified Linear Bandits? ICML Jialin Dong, Lin Yang
2023	A*	`conf`	Efficient Batched Algorithm for Contextual Linear Bandits with Large Action Space via Soft Elimination. NeurIPS Osama A. Hanna, Lin Yang, Christina Fragouli
2023	—	`conf`	MetaVL: Transferring In-Context Learning Ability From Language Models to Vision-Language Models. ACL (2) Masoud Monajatipoor, Liunian Harold Li, Mozhdeh Rouhsedaghat, Lin Yang, Kai-Wei Chang
2023	A*	`conf`	Provably Efficient Lifelong Reinforcement Learning with Linear Representation. ICLR Sanae Amani, Lin Yang, Ching-An Cheng
2023	A*	`conf`	Replicability in Reinforcement Learning. NeurIPS Amin Karbasi, Grigoris Velegkas, Lin Yang, Felix Zhou
2023	A*	`conf`	Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds. NeurIPS Jiayi Huang, Han Zhong, Liwei Wang, Lin Yang
2022	J	`jnl`	From Local to Global: Spectral-Inspired Graph Neural Networks. CoRR Ningyuan Huang, Soledad Villar, Carey E. Priebe, Da Zheng, Chengyue Huang, Lin Yang, Vladimir Braverman
2022	A	`conf`	Gap-Dependent Unsupervised Exploration for Reinforcement Learning. AISTATS Jingfeng Wu, Vladimir Braverman, Lin Yang
2022	A*	`conf`	Learning from Distributed Users in Contextual Linear Bandits Without Sharing the Context. NeurIPS Osama A. Hanna, Lin Yang, Christina Fragouli
2022	A*	`conf`	Near-Optimal Reward-Free Exploration for Linear Mixture MDPs with Plug-in Solver. ICLR Xiaoyu Chen, Jiachen Hu, Lin Yang, Liwei Wang
2022	A*	`conf`	Near-Optimal Sample Complexity Bounds for Constrained MDPs. NeurIPS Sharan Vaswani, Lin Yang, Csaba Szepesvári
2022	A*	`conf`	On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning. ICML Weichao Mao, Lin Yang, Kaiqing Zhang, Tamer Basar
2022	A*	`conf`	Provably Feedback-Efficient Reinforcement Learning via Active Reward Learning. NeurIPS Dingwen Kong, Lin Yang
2022	A	`conf`	Solving Multi-Arm Bandit Using a Few Bits of Communication. AISTATS Osama A. Hanna, Lin Yang, Christina Fragouli
2021	A*	`conf`	Accommodating Picky Customers: Regret Bound and Exploration Complexity for Multi-Objective Reinforcement Learning. NeurIPS Jingfeng Wu, Vladimir Braverman, Lin Yang
2021	A*	`conf`	Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs. NeurIPS Han Zhong, Jiayi Huang, Lin Yang, Liwei Wang
2021	A*	`conf`	On the Value of Interaction and Function Approximation in Imitation Learning. NeurIPS Nived Rajaraman, Yanjun Han, Lin Yang, Jingbo Liu, Jiantao Jiao, Kannan Ramchandran
2021	A*	`conf`	Provably Correct Optimization and Exploration with Non-linear Policies. ICML Fei Feng, Wotao Yin, Alekh Agarwal, Lin Yang
2021	A*	`conf`	Randomized Exploration in Reinforcement Learning with General Value Function Approximation. ICML Haque Ishfaq, Qiwen Cui, Viet Nguyen, Alex Ayoub, Zhuoran Yang, Zhaoran Wang, Doina Precup, Lin Yang
2021	A*	`conf`	Safe Reinforcement Learning with Linear Function Approximation. ICML Sanae Amani, Christos Thrampoulidis, Lin Yang
2020	A*	`conf`	Model-Based Reinforcement Learning with Value-Targeted Regression. ICML Alex Ayoub, Zeyu Jia, Csaba Szepesvári, Mengdi Wang, Lin Yang
2020	—	`conf`	Model-Based Reinforcement Learning with Value-Targeted Regression. L4DC Zeyu Jia, Lin Yang, Csaba Szepesvári, Mengdi Wang
2020	A*	`conf`	Nearly Linear Row Sampling Algorithm for Quantile Regression. ICML Yi Li, Ruosong Wang, Lin Yang, Hanrui Zhang
2020	J	`jnl`	Nearly Linear Row Sampling Algorithm for Quantile Regression. CoRR Yi Li, Ruosong Wang, Lin Yang, Hanrui Zhang
2020	A*	`conf`	Obtaining Adjustable Regularization for Free via Iterate Averaging. ICML Jingfeng Wu, Vladimir Braverman, Lin Yang
2020	A*	`conf`	Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound. ICML Lin Yang, Mengdi Wang
2020	A	`conf`	Sketching Transformed Matrices with Applications to Natural Language Processing. AISTATS Yingyu Liang, Zhao Song, Mengdi Wang, Lin Yang, Xin Yang
2020	A	`conf`	Solving Discounted Stochastic Two-Player Games with Near-Optimal Time and Sample Complexity. AISTATS Aaron Sidford, Mengdi Wang, Lin Yang, Yinyu Ye
2019	A	`conf`	On Constrained Nonconvex Stochastic Optimization: A Case Study for Generalized Eigenvalue Decomposition. AISTATS Zhehui Chen, Xingguo Li, Lin Yang, Jarvis D. Haupt, Tuo Zhao
2019	A*	`conf`	Sample-Optimal Parametric Q-Learning Using Linearly Additive Features. ICML Lin Yang, Mengdi Wang
2018	A*	`conf`	Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization. NeurIPS Minshuo Chen, Lin Yang, Mengdi Wang, Tuo Zhao
2018	J	`jnl`	Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization. CoRR Minshuo Chen, Lin Yang, Mengdi Wang, Tuo Zhao
2018	A*	`conf`	Near-Optimal Time and Sample Complexities for Solving Markov Decision Processes with a Generative Model. NeurIPS Aaron Sidford, Mengdi Wang, Xian Wu, Lin Yang, Yinyu Ye
2017	—	`conf`	On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning. NIPS Xingguo Li, Lin Yang, Jason Ge, Jarvis D. Haupt, Tong Zhang, Tuo Zhao
2015	B	`conf`	Streaming Algorithms for Halo Finders. e-Science Zaoxing Liu, Nikita Ivkin, Lin Yang, Mark Neyrinck, Gerard Lemson, Alexander S. Szalay, Vladimir Braverman, Tamas Budavari, Randal C. Burns, Xin Wang
2013	—	`—`	Mathematical Theories of Interaction with Oracles. Lin Yang