Bypassing the Monster: A Faster and Simpler Optimal Algorithm for Contextual Bandits under Realizability

28 March 2020

Papers citing "Bypassing the Monster: A Faster and Simpler Optimal Algorithm for Contextual Bandits under Realizability"

24 / 24 papers shown

Title
Constrained Online Decision-Making: A Unified Framework Haichen Hu David Simchi-Levi Navid Azizan 31 0 0 11 May 2025
Greedy Algorithm for Structured Bandits: A Sharp Characterization of Asymptotic Success / Failure Aleksandrs Slivkins Yunzong Xu Shiliang Zuo 72 1 0 06 Mar 2025
Online Planning of Power Flows for Power Systems Against Bushfires Using Spatial Context Jianyu Xu Qiuzhuang Sun Yang Yang Huadong Mo Daoyi Dong 75 0 0 24 Feb 2025
On The Statistical Complexity of Offline Decision-Making Thanh Nguyen-Tang R. Arora OffRL 43 1 0 10 Jan 2025
Generalized Linear Bandits with Limited Adaptivity Ayush Sawarni Nirjhar Das Siddharth Barman Gaurav Sinha 37 3 0 10 Apr 2024
Agnostic Interactive Imitation Learning: New Theory and Practical Algorithms Yichen Li Chicheng Zhang OffRL 31 0 0 28 Dec 2023
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
Stochastic Graph Bandit Learning with Side-Observations Xueping Gong Jiheng Zhang 26 1 0 29 Aug 2023
Sequential Counterfactual Risk Minimization Houssam Zenati Eustache Diemert Matthieu Martin Julien Mairal Pierre Gaillard OffRL 21 3 0 23 Feb 2023
Infinite Action Contextual Bandits with Reusable Data Exhaust Mark Rucker Yinglun Zhu Paul Mineiro OffRL 21 1 0 16 Feb 2023
Learning to Generate All Feasible Actions Mirco Theile Daniele Bernardini Raphael Trumpp C. Piazza Marco Caccamo Alberto L. Sangiovanni-Vincentelli 29 2 0 26 Jan 2023
Contextual Bandits in a Survey Experiment on Charitable Giving: Within-Experiment Outcomes versus Policy Learning Susan Athey Undral Byambadalai Vitor Hadad Sanath Kumar Krishnamurthy Weiwen Leung Joseph Jay Williams 27 13 0 22 Nov 2022
Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees Andrea Tirinzoni Matteo Papini Ahmed Touati A. Lazaric Matteo Pirotta 28 4 0 24 Oct 2022
Optimal Contextual Bandits with Knapsacks under Realizability via Regression Oracles Yuxuan Han Jialin Zeng Yang Wang Yangzhen Xiang Jiheng Zhang 51 9 0 21 Oct 2022
$Breaking the $\sqrt{T}$ Barrier: Instance-Independent Logarithmic Regret in Stochastic Contextual Linear Bandits$ Breaking the $\sqrt{T}$ Barrier: Instance-Independent Logarithmic Regret in Stochastic Contextual Linear Bandits Avishek Ghosh Abishek Sankararaman 21 3 0 19 May 2022
Jump-Start Reinforcement Learning Ikechukwu Uchendu Ted Xiao Yao Lu Banghua Zhu Mengyuan Yan ... Chuyuan Fu Cong Ma Jiantao Jiao Sergey Levine Karol Hausman OffRL OnRL 33 109 0 05 Apr 2022
Efficient Active Learning with Abstention Yinglun Zhu Robert D. Nowak 49 11 0 31 Mar 2022
Flexible and Efficient Contextual Bandits with Heterogeneous Treatment Effect Oracles Aldo G. Carranza Sanath Kumar Krishnamurthy Susan Athey 11 1 0 30 Mar 2022
Oracle-Efficient Online Learning for Beyond Worst-Case Adversaries Nika Haghtalab Yanjun Han Abhishek Shetty Kunhe Yang 32 23 0 17 Feb 2022
Recent Advances in Reinforcement Learning in Finance B. Hambly Renyuan Xu Huining Yang OffRL 27 166 0 08 Dec 2021
Feel-Good Thompson Sampling for Contextual Bandits and Reinforcement Learning Tong Zhang 22 63 0 02 Oct 2021
On component interactions in two-stage recommender systems Jiri Hron K. Krauth Michael I. Jordan Niki Kilbertus CML LRM 32 31 0 28 Jun 2021
Linear Bandits with Limited Adaptivity and Learning Distributional Optimal Design Yufei Ruan Jiaqi Yang Yuanshuo Zhou OffRL 92 50 0 04 Jul 2020
Learning without Concentration S. Mendelson 85 334 0 01 Jan 2014