Information Directed Sampling and Bandits with Heteroscedastic Noise

29 January 2018

Papers citing "Information Directed Sampling and Bandits with Heteroscedastic Noise"

22 / 22 papers shown

Title
Improved Regret Analysis in Gaussian Process Bandits: Optimality for Noiseless Reward, RKHS norm, and Non-Stationary Variance S. Iwazaki Shion Takeno 76 1 0 10 Feb 2025
Second Order Bounds for Contextual Bandits with Function Approximation Aldo Pacchiano 42 4 0 24 Sep 2024
A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits Junghyun Lee Se-Young Yun Kwang-Sung Jun 28 4 0 19 Jul 2024
Variance-Dependent Regret Bounds for Non-stationary Linear Bandits Zhiyong Wang Jize Xie Yi Chen J. C. Lui Dongruo Zhou 28 0 0 15 Mar 2024
TS-RSR: A provably efficient approach for batch bayesian optimization Zhaolin Ren Na Li 29 2 0 07 Mar 2024
BOF-UCB: A Bayesian-Optimistic Frequentist Algorithm for Non-Stationary Contextual Bandits Nicklas Werge Abdullah Akgul M. Kandemir 33 0 0 07 Jul 2023
Geometry-Aware Approaches for Balancing Performance and Theoretical Guarantees in Linear Bandits Yuwei Luo Mohsen Bayati 10 1 0 26 Jun 2023
SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits Subhojyoti Mukherjee Qiaomin Xie Josiah P. Hanna R. Nowak OffRL 39 5 0 29 Jan 2023
Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes Jiafan He Heyang Zhao Dongruo Zhou Quanquan Gu OffRL 33 53 0 12 Dec 2022
Movement Penalized Bayesian Optimization with Application to Wind Energy Systems Shyam Sundhar Ramesh Pier Giuseppe Sessa Andreas Krause Ilija Bogunovic 10 12 0 14 Oct 2022
Active Exploration via Experiment Design in Markov Chains Mojmír Mutný Tadeusz Janik Andreas Krause 31 14 0 29 Jun 2022
Lifting the Information Ratio: An Information-Theoretic Analysis of Thompson Sampling for Contextual Bandits Gergely Neu Julia Olkhovskaya Matteo Papini Ludovic Schwartz 31 16 0 27 May 2022
Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions Jiafan He Dongruo Zhou Tong Zhang Quanquan Gu 61 46 0 13 May 2022
Truncated LinUCB for Stochastic Linear Bandits Yanglei Song Meng zhou 42 0 0 23 Feb 2022
Bayesian Optimization for Distributionally Robust Chance-constrained Problem Yu Inatsu Shion Takeno Masayuki Karasuyama Ichiro Takeuchi 7 13 0 31 Jan 2022
Apple Tasting Revisited: Bayesian Approaches to Partially Monitored Online Binary Classification James A. Grant David S. Leslie 34 3 0 29 Sep 2021
Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain Jianye Hao Tianpei Yang Hongyao Tang Chenjia Bai Jinyi Liu Zhaopeng Meng Peng Liu Zhen Wang OffRL 28 92 0 14 Sep 2021
Metalearning Linear Bandits by Prior Update Amit Peleg Naama Pearl Ron Meir 32 18 0 12 Jul 2021
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning Sebastian Curi Felix Berkenkamp Andreas Krause 20 82 0 15 Jun 2020
Weighted Linear Bandits for Non-Stationary Environments Yoan Russac Claire Vernade Olivier Cappé 82 101 0 19 Sep 2019
Stochastic Bandits with Context Distributions Johannes Kirschner Andreas Krause 13 30 0 06 Jun 2019
Max-value Entropy Search for Efficient Bayesian Optimization Zi Wang Stefanie Jegelka 110 403 0 06 Mar 2017