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Online Multi-Armed Bandits with Adaptive Inference

25 February 2021

Papers citing "Online Multi-Armed Bandits with Adaptive Inference"

24 / 24 papers shown

Title
Statistical Inference in Reinforcement Learning: A Selective Survey Chengchun Shi OffRL 238 2 0 22 Feb 2025
A Closer Look at the Worst-case Behavior of Multi-armed Bandit Algorithms Anand Kalvit A. Zeevi 55 34 0 03 Jun 2021
Off-Policy Evaluation via Adaptive Weighting with Data from Contextual Bandits Ruohan Zhan Vitor Hadad David A. Hirshberg Susan Athey OffRL 77 62 0 03 Jun 2021
Inference for Batched Bandits Kelly W. Zhang Lucas Janson Susan Murphy 76 85 0 08 Feb 2020
Confidence Intervals for Policy Evaluation in Adaptive Experiments Vitor Hadad David A. Hirshberg Ruohan Zhan Stefan Wager Susan Athey 66 146 0 07 Nov 2019
On the bias, risk and consistency of sample means in multi-armed bandits Jaehyeok Shin Aaditya Ramdas Alessandro Rinaldo 59 37 0 02 Feb 2019
Balanced Linear Contextual Bandits Maria Dimakopoulou Zhengyuan Zhou Susan Athey Guido Imbens 51 65 0 15 Dec 2018
Mitigating Bias in Adaptive Data Gathering via Differential Privacy Seth Neel Aaron Roth FedML 66 37 0 06 Jun 2018
A Contextual Bandit Bake-off A. Bietti Alekh Agarwal John Langford 351 105 0 12 Feb 2018
Estimation Considerations in Contextual Bandits Maria Dimakopoulou Zhengyuan Zhou Susan Athey Guido Imbens 274 69 0 19 Nov 2017
Why Adaptively Collected Data Have Negative Bias and How to Correct for It Xinkun Nie Xiaoying Tian Jonathan E. Taylor James Zou OnRL 68 90 0 07 Aug 2017
Thompson Sampling for the MNL-Bandit Shipra Agrawal Vashist Avadhanula Vineet Goyal A. Zeevi 130 98 0 03 Jun 2017
Scalable Generalized Linear Bandits: Online Computation and Hashing Kwang-Sung Jun Aniruddha Bhargava Robert D. Nowak Rebecca Willett 74 124 0 01 Jun 2017
Statistical inference for the mean outcome under a possibly non-unique optimal treatment strategy Alexander Luedtke M. J. van der Laan 260 222 0 24 Mar 2016
Simple Bayesian Algorithms for Best Arm Identification Daniel Russo 62 280 0 26 Feb 2016
Upper-Confidence-Bound Algorithms for Active Learning in Multi-Armed Bandits Alexandra Carpentier A. Lazaric Mohammad Ghavamzadeh Rémi Munos P. Auer András Antos 41 98 0 16 Jul 2015
An Information-Theoretic Analysis of Thompson Sampling Daniel Russo Benjamin Van Roy 161 426 0 21 Mar 2014
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits Alekh Agarwal Daniel J. Hsu Satyen Kale John Langford Lihong Li Robert Schapire OffRL 394 509 0 04 Feb 2014
Learning to Optimize Via Posterior Sampling Daniel Russo Benjamin Van Roy 200 702 0 11 Jan 2013
Further Optimal Regret Bounds for Thompson Sampling Shipra Agrawal Navin Goyal 107 442 0 15 Sep 2012
Thompson Sampling for Contextual Bandits with Linear Payoffs Shipra Agrawal Navin Goyal 195 1,004 0 15 Sep 2012
Thompson Sampling: An Asymptotically Optimal Finite Time Analysis E. Kaufmann N. Korda Rémi Munos 162 588 0 18 May 2012
The KL-UCB Algorithm for Bounded Stochastic Bandits and Beyond Aurélien Garivier Olivier Cappé 177 613 0 12 Feb 2011
A Contextual-Bandit Approach to Personalized News Article Recommendation Lihong Li Wei Chu John Langford Robert Schapire 471 2,954 0 28 Feb 2010