Papers citing 'On Online Learning in Kernelized Markov Decision Processes'

Title
Computationally and Sample Efficient Safe Reinforcement Learning Using Adaptive Conformal Prediction Hao Zhou Yanze Zhang Wenhao Luo 133 2 0 22 Mar 2025
Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs Davide Maran Alberto Maria Metelli Matteo Papini Marcello Restelli 126 0 0 31 Oct 2024
Provably Adaptive Average Reward Reinforcement Learning for Metric Spaces Avik Kar Rahul Singh 114 0 0 25 Oct 2024
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling Jasmine Bayrooti Carl Henrik Ek Amanda Prorok 273 0 0 07 Oct 2024
Causal Bayesian Optimization via Exogenous Distribution Learning Shaogang Ren Xiaoning Qian 226 2 0 03 Feb 2024
Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning Ahmadreza Moradipari M. Pedramfar Modjtaba Shokrian Zini Vaneet Aggarwal 144 6 0 30 Oct 2023
Efficient Exploration in Continuous-time Model-based Reinforcement Learning Lenart Treven Jonas Hübotter Bhavya Sukhija Florian Dorfler Andreas Krause 135 11 0 30 Oct 2023
Distributionally Robust Model-based Reinforcement Learning with Large State Spaces Shyam Sundhar Ramesh Pier Giuseppe Sessa Yifan Hu Andreas Krause Ilija Bogunovic OOD 128 17 0 05 Sep 2023
Safe Model-Based Multi-Agent Mean-Field Reinforcement Learning Matej Jusup Barna Pásztor Tadeusz Janik Kecheng Zhang Francesco Corman Andreas Krause Ilija Bogunovic 167 4 0 29 Jun 2023
Kernelized Reinforcement Learning with Order Optimal Regret Bounds Sattar Vakili Julia Olkhovskaya 154 10 0 13 Jun 2023
STEERING: Stein Information Directed Exploration for Model-Based Reinforcement Learning Souradip Chakraborty Amrit Singh Bedi Alec Koppel Mengdi Wang Furong Huang Dinesh Manocha 94 8 0 28 Jan 2023
Model-based Causal Bayesian Optimization Scott Sussex A. Makarova Andreas Krause CML 121 28 0 18 Nov 2022
Movement Penalized Bayesian Optimization with Application to Wind Energy Systems Shyam Sundhar Ramesh Pier Giuseppe Sessa Andreas Krause Ilija Bogunovic 113 12 0 14 Oct 2022
Bilinear Exponential Family of MDPs: Frequentist Regret Bound with Tractable Exploration and Planning Reda Ouhamma D. Basu Odalric-Ambrym Maillard OffRL 115 12 0 05 Oct 2022
Conservative Dual Policy Optimization for Efficient Model-Based Reinforcement Learning Shen Zhang 94 6 0 16 Sep 2022
Model Selection in Reinforcement Learning with General Function Approximations Avishek Ghosh Sayak Ray Chowdhury 74 3 0 06 Jul 2022
Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning Souradip Chakraborty Amrit Singh Bedi Alec Koppel Brian M. Sadler Furong Huang Erfaun Noorani Tianyi Zhou 124 9 0 02 Jun 2022
Provably Efficient Kernelized Q-Learning Shuang Liu H. Su MLT 132 4 0 21 Apr 2022
Differentially Private Regret Minimization in Episodic Markov Decision Processes Sayak Ray Chowdhury Xingyu Zhou 118 23 0 20 Dec 2021
Representation Learning for Online and Offline RL in Low-rank MDPs Masatoshi Uehara Xuezhou Zhang Wen Sun OffRL 292 132 0 09 Oct 2021
Adaptive Control of Differentially Private Linear Quadratic Systems Sayak Ray Chowdhury Xingyu Zhou Ness B. Shroff 91 10 0 26 Aug 2021
Model Selection for Generic Reinforcement Learning Avishek Ghosh Sayak Ray Chowdhury Kannan Ramchandran 102 1 0 13 Jul 2021
Efficient Model-Based Multi-Agent Mean-Field Reinforcement Learning Barna Pásztor Ilija Bogunovic Andreas Krause 151 46 0 08 Jul 2021
Mitigating Covariate Shift in Imitation Learning via Offline Data Without Great Coverage Jonathan D. Chang Masatoshi Uehara Dhruv Sreenivas Rahul Kidambi Wen Sun OffRL 177 36 0 06 Jun 2021
Learning Good State and Action Representations via Tensor Decomposition Chengzhuo Ni Yaqi Duan M. Dahleh Anru R. Zhang Mengdi Wang 133 7 0 03 May 2021
Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning Sebastian Curi Ilija Bogunovic Andreas Krause 113 18 0 18 Mar 2021
Policy Optimization as Online Learning with Mediator Feedback Alberto Maria Metelli Matteo Papini P. DÓro Marcello Restelli OffRL 115 11 0 15 Dec 2020
Model-based Reinforcement Learning for Continuous Control with Posterior SamplingInternational Conference on Machine Learning (ICML), 2024 Ying Fan Yifei Ming 169 19 0 20 Nov 2020
Value Function Approximations via Kernel Embeddings for No-Regret Reinforcement Learning Sayak Ray Chowdhury Rafael Oliveira OffRL 148 5 0 16 Nov 2020
No-regret Algorithms for Multi-task Bayesian OptimizationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2025 Sayak Ray Chowdhury Aditya Gopalan 89 18 0 20 Aug 2020
Information Theoretic Regret Bounds for Online Nonlinear ControlNeural Information Processing Systems (NeurIPS), 2025 Sham Kakade A. Krishnamurthy Kendall Lowrey Motoya Ohnishi Wen Sun 135 121 0 22 Jun 2020
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and PlanningNeural Information Processing Systems (NeurIPS), 2025 Sebastian Curi Felix Berkenkamp Andreas Krause 237 90 0 15 Jun 2020
Kernel-Based Reinforcement Learning: A Finite-Time Analysis O. D. Domingues Pierre Ménard Matteo Pirotta E. Kaufmann Michal Valko 112 20 0 12 Apr 2020
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound Lin F. Yang Mengdi Wang OffRL GP 229 294 0 24 May 2019
Online Learning in Kernelized Markov Decision Processes Sayak Ray Chowdhury Aditya Gopalan OffRL 107 3 0 21 May 2018