Ensemble Sampling

20 May 2017

Papers citing "Ensemble Sampling"

39 / 39 papers shown

Title
Generalization in Monitored Markov Decision Processes (Mon-MDPs) Montaser Mohammedalamen Michael Bowling 34 0 0 13 May 2025
Toward Efficient Exploration by Large Language Model Agents Dilip Arumugam Thomas L. Griffiths LLMAG 94 1 0 29 Apr 2025
Improved Regret of Linear Ensemble Sampling Harin Lee Min-hwan Oh 42 1 0 06 Nov 2024
Bayesian Bandit Algorithms with Approximate Inference in Stochastic Linear Bandits Ziyi Huang Henry Lam Haofeng Zhang 38 0 0 20 Jun 2024
Online Bandit Learning with Offline Preference Data for Improved RLHF Akhil Agnihotri Rahul Jain Deepak Ramachandran Zheng Wen OffRL 47 2 0 13 Jun 2024
Improving sample efficiency of high dimensional Bayesian optimization with MCMC Zeji Yi Yunyue Wei Chu Xin Cheng Kaibo He Yanan Sui 30 5 0 05 Jan 2024
Ensemble sampling for linear bandits: small ensembles suffice David Janz A. Litvak Csaba Szepesvári 38 1 0 14 Nov 2023
VITS : Variational Inference Thompson Sampling for contextual bandits Pierre Clavier Tom Huix Alain Durmus 29 3 0 19 Jul 2023
Neural Exploitation and Exploration of Contextual Bandits Yikun Ban Yuchen Yan A. Banerjee Jingrui He 44 8 0 05 May 2023
Multiplier Bootstrap-based Exploration Runzhe Wan Haoyu Wei Branislav Kveton R. Song 21 3 0 03 Feb 2023
Deep Active Ensemble Sampling For Image Classification S. Mohamadi Gianfranco Doretto Donald Adjeroh UQCV 21 9 0 11 Oct 2022
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity Alekh Agarwal Tong Zhang 55 22 0 15 Jun 2022
Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping Vikranth Dwaracherla Zheng Wen Ian Osband Xiuyuan Lu S. Asghari Benjamin Van Roy UQCV 32 18 0 08 Jun 2022
Lifting the Information Ratio: An Information-Theoretic Analysis of Thompson Sampling for Contextual Bandits Gergely Neu Julia Olkhovskaya Matteo Papini Ludovic Schwartz 38 16 0 27 May 2022
An Analysis of Ensemble Sampling Chao Qin Zheng Wen Xiuyuan Lu Benjamin Van Roy 37 21 0 02 Mar 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
SUPER-Net: Trustworthy Medical Image Segmentation with Uncertainty Propagation in Encoder-Decoder Networks Giuseppina Carannante Dimah Dera Nidhal C.Bouaynaya Hassan M. Fathallah-Shaykh Ghulam Rasool UQCV AAML OOD 27 6 0 10 Nov 2021
Learning to Be Cautious Montaser Mohammedalamen Dustin Morrill Alexander Sieusahai Yash Satsangi Michael Bowling 18 3 0 29 Oct 2021
The Value of Information When Deciding What to Learn Dilip Arumugam Benjamin Van Roy 37 12 0 26 Oct 2021
Anti-Concentrated Confidence Bonuses for Scalable Exploration Jordan T. Ash Cyril Zhang Surbhi Goel A. Krishnamurthy Sham Kakade 48 6 0 21 Oct 2021
EE-Net: Exploitation-Exploration Neural Networks in Contextual Bandits Yikun Ban Yuchen Yan A. Banerjee Jingrui He OffRL 39 39 0 07 Oct 2021
Deep Exploration for Recommendation Systems Zheqing Zhu Benjamin Van Roy 37 11 0 26 Sep 2021
Information Directed Sampling for Sparse Linear Bandits Botao Hao Tor Lattimore Wei Deng 25 19 0 29 May 2021
Policy Optimization as Online Learning with Mediator Feedback Alberto Maria Metelli Matteo Papini P. DÓro Marcello Restelli OffRL 27 10 0 15 Dec 2020
Randomized Value Functions via Posterior State-Abstraction Sampling Dilip Arumugam Benjamin Van Roy OffRL 33 7 0 05 Oct 2020
Neural Thompson Sampling Weitong Zhang Dongruo Zhou Lihong Li Quanquan Gu 34 115 0 02 Oct 2020
Uncertainty-Aware (UNA) Bases for Deep Bayesian Regression Using Multi-Headed Auxiliary Networks Sujay Thakur Cooper Lorsung Yaniv Yacoby Finale Doshi-Velez Weiwei Pan BDL UQCV 33 4 0 21 Jun 2020
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning Sebastian Curi Felix Berkenkamp Andreas Krause 35 82 0 15 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
Model-Based Reinforcement Learning with Value-Targeted Regression Alex Ayoub Zeyu Jia Csaba Szepesvári Mengdi Wang Lin F. Yang OffRL 57 299 0 01 Jun 2020
Ensembled sparse-input hierarchical networks for high-dimensional datasets Jean Feng N. Simon 19 4 0 11 May 2020
Behaviour Suite for Reinforcement Learning Ian Osband Yotam Doron Matteo Hessel John Aslanides Eren Sezener ... Satinder Singh Benjamin Van Roy R. Sutton David Silver H. V. Hasselt OffRL 32 178 0 09 Aug 2019
Perturbed-History Exploration in Stochastic Linear Bandits Branislav Kveton Csaba Szepesvári Mohammad Ghavamzadeh Craig Boutilier 24 41 0 21 Mar 2019
Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits Branislav Kveton Csaba Szepesvári Sharan Vaswani Zheng Wen Mohammad Ghavamzadeh Tor Lattimore 15 69 0 13 Nov 2018
Randomized Prior Functions for Deep Reinforcement Learning Ian Osband John Aslanides Albin Cassirer UQCV BDL 21 372 0 08 Jun 2018
Practical Contextual Bandits with Regression Oracles Dylan J. Foster Alekh Agarwal Miroslav Dudík Haipeng Luo Robert Schapire 16 124 0 03 Mar 2018
Coordinated Exploration in Concurrent Reinforcement Learning Maria Dimakopoulou Benjamin Van Roy 31 40 0 05 Feb 2018
Deep Exploration via Randomized Value Functions Ian Osband Benjamin Van Roy Daniel Russo Zheng Wen 41 300 0 22 Mar 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 289 9,167 0 06 Jun 2015