Learning to Optimize Via Posterior Sampling

11 January 2013

Papers citing "Learning to Optimize Via Posterior Sampling"

50 / 147 papers shown

Title
Deep Hierarchy in Bandits Joey Hong Branislav Kveton S. Katariya Manzil Zaheer Mohammad Ghavamzadeh 33 20 0 03 Feb 2022
Meta-Learning Hypothesis Spaces for Sequential Decision-making Parnian Kassraie Jonas Rothfuss Andreas Krause OffRL 47 6 0 01 Feb 2022
Optimal Regret Is Achievable with Bounded Approximate Inference Error: An Enhanced Bayesian Upper Confidence Bound Framework Ziyi Huang Henry Lam A. Meisami Haofeng Zhang 41 4 0 31 Jan 2022
Gaussian Imagination in Bandit Learning Yueyang Liu Adithya M. Devraj Benjamin Van Roy Kuang Xu 40 7 0 06 Jan 2022
A Free Lunch from the Noise: Provable and Practical Exploration for Representation Learning Tongzheng Ren Tianjun Zhang Csaba Szepesvári Bo Dai 39 19 0 22 Nov 2021
Hierarchical Bayesian Bandits Joey Hong Branislav Kveton Manzil Zaheer Mohammad Ghavamzadeh FedML 52 38 0 12 Nov 2021
Solving Multi-Arm Bandit Using a Few Bits of Communication Osama A. Hanna Lin F. Yang Christina Fragouli 29 16 0 11 Nov 2021
Online Learning of Energy Consumption for Navigation of Electric Vehicles Niklas Åkerblom Yuxin Chen M. Chehreghani 30 12 0 03 Nov 2021
Analysis of Thompson Sampling for Partially Observable Contextual Multi-Armed Bandits Yash J. Patel Mohamad Kazem Shirani Faradonbeh 16 15 0 23 Oct 2021
Representation Learning for Online and Offline RL in Low-rank MDPs Masatoshi Uehara Xuezhou Zhang Wen Sun OffRL 67 127 0 09 Oct 2021
Feel-Good Thompson Sampling for Contextual Bandits and Reinforcement Learning Tong Zhang 27 63 0 02 Oct 2021
Apple Tasting Revisited: Bayesian Approaches to Partially Monitored Online Binary Classification James A. Grant David S. Leslie 50 3 0 29 Sep 2021
Online Learning of Network Bottlenecks via Minimax Paths Niklas Åkerblom F. Hoseini M. Chehreghani 37 10 0 17 Sep 2021
Metadata-based Multi-Task Bandits with Bayesian Hierarchical Models Runzhe Wan Linjuan Ge Rui Song 38 28 0 13 Aug 2021
Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability Dibya Ghosh Jad Rahme Aviral Kumar Amy Zhang Ryan P. Adams Sergey Levine OffRL 286 109 0 13 Jul 2021
No Regrets for Learning the Prior in Bandits Soumya Basu Branislav Kveton Manzil Zaheer Csaba Szepesvári 46 33 0 13 Jul 2021
Metalearning Linear Bandits by Prior Update Amit Peleg Naama Pearl Ron Meir 42 18 0 12 Jul 2021
Information Directed Sampling for Sparse Linear Bandits Botao Hao Tor Lattimore Wei Deng 25 19 0 29 May 2021
Policy Learning with Adaptively Collected Data Ruohan Zhan Zhimei Ren Susan Athey Zhengyuan Zhou OffRL 45 27 0 05 May 2021
When and Whom to Collaborate with in a Changing Environment: A Collaborative Dynamic Bandit Solution Chuanhao Li Qingyun Wu Hongning Wang 50 5 0 14 Apr 2021
UCB-based Algorithms for Multinomial Logistic Regression Bandits Sanae Amani Christos Thrampoulidis 34 10 0 21 Mar 2021
Reinforcement Learning, Bit by Bit Xiuyuan Lu Benjamin Van Roy Vikranth Dwaracherla M. Ibrahimi Ian Osband Zheng Wen 30 70 0 06 Mar 2021
Fairness of Exposure in Stochastic Bandits Lequn Wang Yiwei Bai Wen Sun Thorsten Joachims FaML 29 49 0 03 Mar 2021
Online Multi-Armed Bandits with Adaptive Inference Maria Dimakopoulou Zhimei Ren Zhengyuan Zhou 40 34 0 25 Feb 2021
Online Learning for Unknown Partially Observable MDPs Mehdi Jafarnia-Jahromi Rahul Jain A. Nayyar 39 20 0 25 Feb 2021
Bayesian adversarial multi-node bandit for optimal smart grid protection against cyber attacks Jianyu Xu Bin Liu H. Mo D. Dong AAML 16 22 0 20 Feb 2021
The Elliptical Potential Lemma for General Distributions with an Application to Linear Thompson Sampling N. Hamidi Mohsen Bayati 22 1 0 16 Feb 2021
Meta-Thompson Sampling Branislav Kveton Mikhail Konobeev Manzil Zaheer Chih-Wei Hsu Martin Mladenov Craig Boutilier Csaba Szepesvári 50 61 0 11 Feb 2021
Non-Stationary Latent Bandits Joey Hong Branislav Kveton Manzil Zaheer Yinlam Chow Amr Ahmed Mohammad Ghavamzadeh Craig Boutilier OffRL 38 13 0 01 Dec 2020
Model-based Reinforcement Learning for Continuous Control with Posterior Sampling Ying Fan Yifei Ming 33 17 0 20 Nov 2020
Asymptotic Convergence of Thompson Sampling Cem Kalkanli Ayfer Özgür 8 5 0 08 Nov 2020
Reinforcement Learning for Efficient and Tuning-Free Link Adaptation Vidit Saxena H. Tullberg Joakim Jaldén 21 36 0 16 Oct 2020
Neural Thompson Sampling Weitong Zhang Dongruo Zhou Lihong Li Quanquan Gu 34 115 0 02 Oct 2020
On Information Gain and Regret Bounds in Gaussian Process Bandits Sattar Vakili Kia Khezeli Victor Picheny GP 29 128 0 15 Sep 2020
IntelligentPooling: Practical Thompson Sampling for mHealth Sabina Tomkins Peng Liao P. Klasnja Susan Murphy 41 31 0 31 Jul 2020
A Partially Observable MDP Approach for Sequential Testing for Infectious Diseases such as COVID-19 Rahul Singh Fang Liu Ness B. Shroff 23 6 0 25 Jul 2020
Competing Bandits: The Perils of Exploration Under Competition Guy Aridor Yishay Mansour Aleksandrs Slivkins Zhiwei Steven Wu 25 16 0 20 Jul 2020
Information Theoretic Regret Bounds for Online Nonlinear Control Sham Kakade A. Krishnamurthy Kendall Lowrey Motoya Ohnishi Wen Sun 38 117 0 22 Jun 2020
TS-UCB: Improving on Thompson Sampling With Little to No Additional Computation Jackie Baek Vivek F. Farias 45 9 0 11 Jun 2020
Scalable Thompson Sampling using Sparse Gaussian Process Models Sattar Vakili Henry B. Moss A. Artemev Vincent Dutordoir Victor Picheny 13 34 0 09 Jun 2020
Random Hypervolume Scalarizations for Provable Multi-Objective Black Box Optimization Daniel Golovin Qiuyi Zhang 33 70 0 08 Jun 2020
Model-Based Reinforcement Learning with Value-Targeted Regression Alex Ayoub Zeyu Jia Csaba Szepesvári Mengdi Wang Lin F. Yang OffRL 59 299 0 01 Jun 2020
Seamlessly Unifying Attributes and Items: Conversational Recommendation for Cold-Start Users Shijun Li Wenqiang Lei Qingyun Wu Xiangnan He Peng Jiang Tat-Seng Chua 31 118 0 23 May 2020
Online Learning and Optimization for Revenue Management Problems with Add-on Discounts D. Simchi-Levi Rui Sun Huanan Zhang 16 11 0 02 May 2020
Sequential Batch Learning in Finite-Action Linear Contextual Bandits Yanjun Han Zhengqing Zhou Zhengyuan Zhou Jose H. Blanchet Peter Glynn Yinyu Ye OffRL 9 71 0 14 Apr 2020
Online Residential Demand Response via Contextual Multi-Armed Bandits Xin Chen Yutong Nie Na Li 16 30 0 07 Mar 2020
Improved Optimistic Algorithms for Logistic Bandits Louis Faury Marc Abeille Clément Calauzènes Olivier Fercoq 23 85 0 18 Feb 2020
Bayesian Optimization for Categorical and Category-Specific Continuous Inputs Dang Nguyen Sunil R. Gupta Santu Rana A. Shilton Svetha Venkatesh 16 50 0 28 Nov 2019
Comments on the Du-Kakade-Wang-Yang Lower Bounds Benjamin Van Roy Shi Dong 22 38 0 18 Nov 2019
Neural Contextual Bandits with UCB-based Exploration Dongruo Zhou Lihong Li Quanquan Gu 38 15 0 11 Nov 2019