Tight Guarantees for Interactive Decision Making with the Decision-Estimation Coefficient

19 January 2023

Papers citing "Tight Guarantees for Interactive Decision Making with the Decision-Estimation Coefficient"

24 / 24 papers shown

Title
Evolution of Information in Interactive Decision Making: A Case Study for Multi-Armed Bandits Yuzhou Gu Yanjun Han Jian Qian 31 0 0 01 Mar 2025
Near-Optimal Private Learning in Linear Contextual Bandits Fan Chen Jiachun Li Alexander Rakhlin D. Simchi-Levi 46 1 0 18 Feb 2025
Decision Making in Hybrid Environments: A Model Aggregation Approach Haolin Liu Chen-Yu Wei Julian Zimmert 86 0 0 09 Feb 2025
A Complete Characterization of Learnability for Stochastic Noisy Bandits Steve Hanneke Kun Wang 35 0 0 20 Jan 2025
Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability Fan Chen Dylan J. Foster Yanjun Han Jian Qian Alexander Rakhlin Yunbei Xu 33 1 0 07 Oct 2024
Misspecified $Q$ -Learning with Sparse Linear Function Approximation: Tight Bounds on Approximation Error Ally Yalei Du Lin F. Yang Ruosong Wang 37 0 0 18 Jul 2024
Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF Tengyang Xie Dylan J. Foster Akshay Krishnamurthy Corby Rosset Ahmed Hassan Awadallah Alexander Rakhlin 49 33 0 31 May 2024
Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation Jianliang He Han Zhong Zhuoran Yang 38 6 0 19 Apr 2024
Provable Interactive Learning with Hindsight Instruction Feedback Dipendra Kumar Misra Aldo Pacchiano Rob Schapire 44 1 0 14 Apr 2024
Regret Minimization via Saddle Point Optimization Johannes Kirschner Seyed Alireza Bakhtiari Kushagra Chandak Volodymyr Tkachuk Csaba Szepesvári 33 1 0 15 Mar 2024
Optimistic Information Directed Sampling Gergely Neu Matteo Papini Ludovic Schwartz 44 2 0 23 Feb 2024
On the Performance of Empirical Risk Minimization with Smoothed Data Adam Block Alexander Rakhlin Abhishek Shetty 39 3 0 22 Feb 2024
Stochastic contextual bandits with graph feedback: from independence number to MAS number Yuxiao Wen Yanjun Han Zhengyuan Zhou 34 1 0 12 Feb 2024
Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation Jiayi Huang Han Zhong Liwei Wang Lin F. Yang 35 2 0 07 Dec 2023
When is Agnostic Reinforcement Learning Statistically Tractable? Zeyu Jia Gene Li Alexander Rakhlin Ayush Sekhari Nathan Srebro OffRL 27 5 0 09 Oct 2023
Bayesian Design Principles for Frequentist Sequential Learning Yunbei Xu A. Zeevi 24 11 0 01 Oct 2023
Efficient Model-Free Exploration in Low-Rank MDPs Zakaria Mhammedi Adam Block Dylan J. Foster Alexander Rakhlin OffRL 24 13 0 08 Jul 2023
Theoretical Hardness and Tractability of POMDPs in RL with Partial Online State Information Ming Shi Yingbin Liang Ness B. Shroff 29 2 0 14 Jun 2023
Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration Zhihan Liu Miao Lu Wei Xiong Han Zhong Haotian Hu Shenao Zhang Sirui Zheng Zhuoran Yang Zhaoran Wang OffRL 32 22 0 29 May 2023
Tight Bounds for $γ$ -Regret via the Decision-Estimation Coefficient Margalit Glasgow Alexander Rakhlin OffRL 19 0 0 06 Mar 2023
Statistical Complexity and Optimal Algorithms for Non-linear Ridge Bandits Nived Rajaraman Yanjun Han Jiantao Jiao Kannan Ramchandran 19 1 0 12 Feb 2023
Model-Free Reinforcement Learning with the Decision-Estimation Coefficient Dylan J. Foster Noah Golowich Jian Qian Alexander Rakhlin Ayush Sekhari OffRL 32 9 0 25 Nov 2022
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints Chi Jin Zhuoran Yang Zhaoran Wang OffRL 122 166 0 06 Jan 2021
Kernel-based methods for bandit convex optimization Sébastien Bubeck Ronen Eldan Y. Lee 81 163 0 11 Jul 2016