Learning to Optimize Via Posterior Sampling

11 January 2013

Papers citing "Learning to Optimize Via Posterior Sampling"

47 / 147 papers shown

Title
Safe Linear Thompson Sampling with Side Information Ahmadreza Moradipari Sanae Amani M. Alizadeh Christos Thrampoulidis 27 42 0 06 Nov 2019
Recovering Bandits Ciara Pike-Burke Steffen Grunewalder 15 40 0 31 Oct 2019
Thompson Sampling in Non-Episodic Restless Bandits Young Hun Jung Marc Abeille Ambuj Tewari 9 19 0 12 Oct 2019
Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity Peng Liao Kristjan Greenewald P. Klasnja Susan Murphy 25 83 0 08 Sep 2019
Linear Stochastic Bandits Under Safety Constraints Sanae Amani M. Alizadeh Christos Thrampoulidis 36 117 0 16 Aug 2019
Exploration by Optimisation in Partial Monitoring Tor Lattimore Csaba Szepesvári 33 38 0 12 Jul 2019
Regret Bounds for Thompson Sampling in Episodic Restless Bandit Problems Young Hun Jung Ambuj Tewari 27 44 0 29 May 2019
Connections Between Mirror Descent, Thompson Sampling and the Information Ratio Julian Zimmert Tor Lattimore 30 34 0 28 May 2019
Best Arm Identification in Generalized Linear Bandits Abbas Kazerouni L. Wein 25 29 0 20 May 2019
Adaptive Sensor Placement for Continuous Spaces James A Grant A. Boukouvalas Ryan-Rhys Griffiths David S Leslie Sattar Vakili Enrique Munoz de Cote 29 13 0 16 May 2019
Hedging the Drift: Learning to Optimize under Non-Stationarity Wang Chi Cheung D. Simchi-Levi Ruihao Zhu 35 89 0 04 Mar 2019
Constrained Thompson Sampling for Wireless Link Optimization Vidit Saxena Joseph E. Gonzalez Ion Stoica H. Tullberg Joakim Jaldén 16 7 0 28 Feb 2019
Meta Dynamic Pricing: Transfer Learning Across Experiments Hamsa Bastani D. Simchi-Levi Ruihao Zhu 39 88 0 28 Feb 2019
Learning to Optimize under Non-Stationarity Wang Chi Cheung D. Simchi-Levi Ruihao Zhu 47 133 0 06 Oct 2018
Randomized Prior Functions for Deep Reinforcement Learning Ian Osband John Aslanides Albin Cassirer UQCV BDL 27 372 0 08 Jun 2018
A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations Biswajit Paria Kirthevasan Kandasamy Barnabás Póczós 25 126 0 30 May 2018
An Information-Theoretic Analysis for Thompson Sampling with Many Actions Shi Dong Benjamin Van Roy 14 49 0 30 May 2018
Addressing the Item Cold-start Problem by Attribute-driven Active Learning Y. Zhu Jinhao Lin S. He Beidou Wang Ziyu Guan Haifeng Liu Deng Cai 30 130 0 23 May 2018
PG-TS: Improved Thompson Sampling for Logistic Contextual Bandits Bianca Dumitrascu Karen Feng Barbara E. Engelhardt 19 41 0 18 May 2018
Semiparametric Contextual Bandits A. Krishnamurthy Zhiwei Steven Wu Vasilis Syrgkanis 33 44 0 12 Mar 2018
Multi-objective Contextual Bandit Problem with Similarity Information E. Turğay Doruk Öner Cem Tekin 21 36 0 11 Mar 2018
Reinforcement Learning for Dynamic Bidding in Truckload Markets: an Application to Large-Scale Fleet Management with Advance Commitments Yingfei Wang J. Nascimento Warrren B Powell 18 1 0 25 Feb 2018
Estimation Considerations in Contextual Bandits Maria Dimakopoulou Zhengyuan Zhou Susan Athey Guido Imbens 34 69 0 19 Nov 2017
Multi-objective Contextual Multi-armed Bandit with a Dominant Objective Cem Tekin E. Turğay 36 36 0 18 Aug 2017
On Optimistic versus Randomized Exploration in Reinforcement Learning Ian Osband Benjamin Van Roy 6 10 0 13 Jun 2017
Thompson Sampling for the MNL-Bandit Shipra Agrawal Vashist Avadhanula Vineet Goyal A. Zeevi 35 96 0 03 Jun 2017
Adaptive Rate of Convergence of Thompson Sampling for Gaussian Process Optimization Kinjal Basu Souvik Ghosh 21 42 0 18 May 2017
Multi-dueling Bandits with Dependent Arms Yanan Sui Vincent Zhuang J. W. Burdick Yisong Yue 28 80 0 29 Apr 2017
On Kernelized Multi-armed Bandits Sayak Ray Chowdhury Aditya Gopalan 35 449 0 03 Apr 2017
Deep Exploration via Randomized Value Functions Ian Osband Benjamin Van Roy Daniel Russo Zheng Wen 41 300 0 22 Mar 2017
Provably Optimal Algorithms for Generalized Linear Contextual Bandits Lihong Li Yu Lu Dengyong Zhou 23 94 0 28 Feb 2017
Efficient simulation of high dimensional Gaussian vectors N. Kahalé 14 4 0 28 Feb 2017
Learning to Learn without Gradient Descent by Gradient Descent Yutian Chen Matthew W. Hoffman Sergio Gomez Colmenarejo Misha Denil Timothy Lillicrap Matt Botvinick Nando de Freitas 26 42 0 11 Nov 2016
The End of Optimism? An Asymptotic Analysis of Finite-Armed Linear Bandits Tor Lattimore Csaba Szepesvári 22 103 0 14 Oct 2016
Why is Posterior Sampling Better than Optimism for Reinforcement Learning? Ian Osband Benjamin Van Roy BDL 19 255 0 01 Jul 2016
The Bayesian Linear Information Filtering Problem Bangrui Chen P. Frazier 28 1 0 30 May 2016
Double Thompson Sampling for Dueling Bandits Huasen Wu Xin Liu 22 87 0 25 Apr 2016
Simple Bayesian Algorithms for Best Arm Identification Daniel Russo 31 273 0 26 Feb 2016
On Bayesian index policies for sequential resource allocation E. Kaufmann 46 84 0 06 Jan 2016
Adaptive Ensemble Learning with Confidence Bounds Cem Tekin Jinsung Yoon M. Schaar FedML 19 40 0 23 Dec 2015
A Survey of Online Experiment Design with the Stochastic Multi-Armed Bandit Giuseppe Burtini Jason L. Loeppky Ramon Lawrence 39 119 0 02 Oct 2015
Efficient Learning in Large-Scale Combinatorial Semi-Bandits Zheng Wen Branislav Kveton Azin Ashkan OffRL 59 96 0 28 Jun 2014
An Information-Theoretic Analysis of Thompson Sampling Daniel Russo Benjamin Van Roy 34 421 0 21 Mar 2014
Near-optimal Reinforcement Learning in Factored MDPs Ian Osband Benjamin Van Roy 47 120 0 15 Mar 2014
Generalized Thompson Sampling for Contextual Bandits Lihong Li 29 23 0 27 Oct 2013
Thompson Sampling for 1-Dimensional Exponential Family Bandits N. Korda E. Kaufmann Rémi Munos 29 152 0 12 Jul 2013
(More) Efficient Reinforcement Learning via Posterior Sampling Ian Osband Daniel Russo Benjamin Van Roy 54 525 0 04 Jun 2013