ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2006.12466
  4. Cited By
Information Theoretic Regret Bounds for Online Nonlinear Control

Information Theoretic Regret Bounds for Online Nonlinear Control

22 June 2020
Sham Kakade
A. Krishnamurthy
Kendall Lowrey
Motoya Ohnishi
Wen Sun
ArXivPDFHTML

Papers citing "Information Theoretic Regret Bounds for Online Nonlinear Control"

16 / 16 papers shown
Title
On Bits and Bandits: Quantifying the Regret-Information Trade-off
On Bits and Bandits: Quantifying the Regret-Information Trade-off
Itai Shufaro
Nadav Merlis
Nir Weinberger
Shie Mannor
26
0
0
26 May 2024
Distributionally Robust Model-based Reinforcement Learning with Large
  State Spaces
Distributionally Robust Model-based Reinforcement Learning with Large State Spaces
Shyam Sundhar Ramesh
Pier Giuseppe Sessa
Yifan Hu
Andreas Krause
Ilija Bogunovic
OOD
31
10
0
05 Sep 2023
Optimal Exploration for Model-Based RL in Nonlinear Systems
Optimal Exploration for Model-Based RL in Nonlinear Systems
Andrew Wagenmaker
Guanya Shi
Kevin G. Jamieson
23
14
0
15 Jun 2023
Neural Operators of Backstepping Controller and Observer Gain Functions
  for Reaction-Diffusion PDEs
Neural Operators of Backstepping Controller and Observer Gain Functions for Reaction-Diffusion PDEs
Miroslav Krstic
Luke Bhan
Yuanyuan Shi
36
28
0
18 Mar 2023
Sample Complexity of Kernel-Based Q-Learning
Sample Complexity of Kernel-Based Q-Learning
Sing-Yuan Yeh
Fu-Chieh Chang
Chang-Wei Yueh
Pei-Yuan Wu
A. Bernacchia
Sattar Vakili
OffRL
18
4
0
01 Feb 2023
When to Update Your Model: Constrained Model-based Reinforcement
  Learning
When to Update Your Model: Constrained Model-based Reinforcement Learning
Tianying Ji
Yu-Juan Luo
Fuchun Sun
Mingxuan Jing
Fengxiang He
Wen-bing Huang
8
18
0
15 Oct 2022
Sample-efficient Safe Learning for Online Nonlinear Control with Control
  Barrier Functions
Sample-efficient Safe Learning for Online Nonlinear Control with Control Barrier Functions
Wenhao Luo
Wen Sun
Ashish Kapoor
OffRL
24
9
0
29 Jul 2022
Model-based RL with Optimistic Posterior Sampling: Structural Conditions
  and Sample Complexity
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity
Alekh Agarwal
Tong Zhang
31
22
0
15 Jun 2022
Learning to Control under Time-Varying Environment
Learning to Control under Time-Varying Environment
Yuzhen Han
Rubén Solozabal
Jing Dong
Xingyu Zhou
Martin Takáč
B. Gu
13
2
0
06 Jun 2022
Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement
  Learning
Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning
Chenjia Bai
Lingxiao Wang
Zhuoran Yang
Zhihong Deng
Animesh Garg
Peng Liu
Zhaoran Wang
OffRL
19
132
0
23 Feb 2022
Provable Regret Bounds for Deep Online Learning and Control
Provable Regret Bounds for Deep Online Learning and Control
Xinyi Chen
Edgar Minasyan
Jason D. Lee
Elad Hazan
9
6
0
15 Oct 2021
Stabilizing Dynamical Systems via Policy Gradient Methods
Stabilizing Dynamical Systems via Policy Gradient Methods
Juan C. Perdomo
Jack Umenberger
Max Simchowitz
24
44
0
13 Oct 2021
Representation Learning for Online and Offline RL in Low-rank MDPs
Representation Learning for Online and Offline RL in Low-rank MDPs
Masatoshi Uehara
Xuezhou Zhang
Wen Sun
OffRL
25
125
0
09 Oct 2021
Instrumental Variable Value Iteration for Causal Offline Reinforcement
  Learning
Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning
Luofeng Liao
Zuyue Fu
Zhuoran Yang
Yixin Wang
Mladen Kolar
Zhaoran Wang
OffRL
13
33
0
19 Feb 2021
Active Learning for Nonlinear System Identification with Guarantees
Active Learning for Nonlinear System Identification with Guarantees
Horia Mania
Michael I. Jordan
Benjamin Recht
22
101
0
18 Jun 2020
Efficient Model-Based Reinforcement Learning through Optimistic Policy
  Search and Planning
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning
Sebastian Curi
Felix Berkenkamp
Andreas Krause
12
82
0
15 Jun 2020
1