Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
2306.03739
Cited By
Learning to Do or Learning While Doing: Reinforcement Learning and Bayesian Optimisation for Online Continuous Tuning
6 June 2023
Jan Kaiser
Chenran Xu
Annika Eichler
Andrea Santamaria Garcia
O. Stein
E. Bründermann
W. Kuropka
H. Dinter
F. Mayet
T. Vinatier
F. Burkart
H. Schlarb
OffRL
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Learning to Do or Learning While Doing: Reinforcement Learning and Bayesian Optimisation for Online Continuous Tuning"
9 / 9 papers shown
Title
Learning to Optimize: A Primer and A Benchmark
Tianlong Chen
Xiaohan Chen
Wuyang Chen
Howard Heaton
Jialin Liu
Zhangyang Wang
W. Yin
243
235
0
23 Mar 2021
Deep reinforcement learning for smart calibration of radio telescopes
S. Yatawatta
I. Avruch
33
11
0
05 Feb 2021
Autonomous Control of a Particle Accelerator using Deep Reinforcement Learning
X. Pang
S. Thulasidasan
L. Rybarcyk
34
10
0
16 Oct 2020
Online tuning and light source control using a physics-informed Gaussian process Adi
A. Hanuka
J. Duris
J. Shtalenkova
Dylan Kennedy
A. Edelen
Daniel Ratner
Xiaobiao Huang
37
20
0
04 Nov 2019
Solving Rubik's Cube with a Robot Hand
OpenAI
Ilge Akkaya
Marcin Andrychowicz
Maciek Chociej
Ma-teusz Litwin
...
Peter Welinder
Lilian Weng
Qiming Yuan
Wojciech Zaremba
Lei Zhang
ODL
116
1,232
0
16 Oct 2019
Challenges of Real-World Reinforcement Learning
Gabriel Dulac-Arnold
D. Mankowitz
Todd Hester
OffRL
82
549
0
29 Apr 2019
Addressing Function Approximation Error in Actor-Critic Methods
Scott Fujimoto
H. V. Hoof
David Meger
OffRL
180
5,204
0
26 Feb 2018
Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World
Joshua Tobin
Rachel Fong
Alex Ray
Jonas Schneider
Wojciech Zaremba
Pieter Abbeel
259
2,972
0
20 Mar 2017
Learning to learn by gradient descent by gradient descent
Marcin Andrychowicz
Misha Denil
Sergio Gomez Colmenarejo
Matthew W. Hoffman
David Pfau
Tom Schaul
Brendan Shillingford
Nando de Freitas
115
2,008
0
14 Jun 2016
1