Instance-Dependent Complexity of Contextual Bandits and Reinforcement Learning: A Disagreement-Based Perspective

7 October 2020

Papers citing "Instance-Dependent Complexity of Contextual Bandits and Reinforcement Learning: A Disagreement-Based Perspective"

24 / 24 papers shown

Title
Reinforcement Learning from Human Feedback without Reward Inference: Model-Free Algorithm and Instance-Dependent Analysis Qining Zhang Honghao Wei Lei Ying OffRL 67 1 0 11 Jun 2024
Exploration is Harder than Prediction: Cryptographically Separating Reinforcement Learning from Supervised Learning Noah Golowich Ankur Moitra Dhruv Rohatgi OffRL 35 4 0 04 Apr 2024
Online Learning with Unknown Constraints Karthik Sridharan Seung Won Wilson Yoo 33 2 0 06 Mar 2024
Harnessing the Power of Federated Learning in Federated Contextual Bandits Chengshuai Shi Ruida Zhou Kun Yang Cong Shen FedML 21 0 0 26 Dec 2023
When is Agnostic Reinforcement Learning Statistically Tractable? Zeyu Jia Gene Li Alexander Rakhlin Ayush Sekhari Nathan Srebro OffRL 32 5 0 09 Oct 2023
Stochastic Graph Bandit Learning with Side-Observations Xueping Gong Jiheng Zhang 34 1 0 29 Aug 2023
Does Sparsity Help in Learning Misspecified Linear Bandits? Jialin Dong Lin F. Yang 25 1 0 29 Mar 2023
Smoothed Analysis of Sequential Probability Assignment Alankrita Bhatt Nika Haghtalab Abhishek Shetty 32 9 0 08 Mar 2023
Provably Efficient Reinforcement Learning via Surprise Bound Hanlin Zhu Ruosong Wang Jason D. Lee OffRL 28 5 0 22 Feb 2023
Infinite Action Contextual Bandits with Reusable Data Exhaust Mark Rucker Yinglun Zhu Paul Mineiro OffRL 21 1 0 16 Feb 2023
Efficient Active Learning with Abstention Yinglun Zhu Robert D. Nowak 49 11 0 31 Mar 2022
Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning Approach Xuezhou Zhang Yuda Song Masatoshi Uehara Mengdi Wang Alekh Agarwal Wen Sun OffRL 29 57 0 31 Jan 2022
Efficient and Optimal Algorithms for Contextual Dueling Bandits under Realizability Aadirupa Saha A. Krishnamurthy 34 35 0 24 Nov 2021
Representation Learning for Online and Offline RL in Low-rank MDPs Masatoshi Uehara Xuezhou Zhang Wen Sun OffRL 62 127 0 09 Oct 2021
Efficient First-Order Contextual Bandits: Prediction, Allocation, and Triangular Discrimination Dylan J. Foster A. Krishnamurthy 40 43 0 05 Jul 2021
Provably Efficient Representation Selection in Low-rank Markov Decision Processes: From Online to Offline RL Weitong Zhang Jiafan He Dongruo Zhou Amy Zhang Quanquan Gu OffRL 22 11 0 22 Jun 2021
Randomized Exploration for Reinforcement Learning with General Value Function Approximation Haque Ishfaq Qiwen Cui V. Nguyen Alex Ayoub Zhuoran Yang Zhaoran Wang Doina Precup Lin F. Yang 32 43 0 15 Jun 2021
The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces Chi Jin Qinghua Liu Tiancheng Yu 26 50 0 07 Jun 2021
Model-free Representation Learning and Exploration in Low-rank MDPs Aditya Modi Jinglin Chen A. Krishnamurthy Nan Jiang Alekh Agarwal OffRL 102 78 0 14 Feb 2021
Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms Chi Jin Qinghua Liu Sobhan Miryoosefi OffRL 35 213 0 01 Feb 2021
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints Chi Jin Zhuoran Yang Zhaoran Wang OffRL 122 166 0 06 Jan 2021
Fast Rates for Contextual Linear Optimization Yichun Hu Nathan Kallus Xiaojie Mao OffRL 34 41 0 05 Nov 2020
Bypassing the Monster: A Faster and Simpler Optimal Algorithm for Contextual Bandits under Realizability D. Simchi-Levi Yunzong Xu OffRL 47 107 0 28 Mar 2020
Optimism in Reinforcement Learning with Generalized Linear Function Approximation Yining Wang Ruosong Wang S. Du A. Krishnamurthy 135 135 0 09 Dec 2019