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Learning to Guide Random Search

Learning to Guide Random Search

Ozan Sener
V. Koltun
    ODL
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Papers citing "Learning to Guide Random Search"

7 / 7 papers shown
Title
Generalizing Gaussian Smoothing for Random Search
Generalizing Gaussian Smoothing for Random Search
Katelyn Gao
Ozan Sener
80
14
0
27 Nov 2022
Pareto Set Learning for Expensive Multi-Objective Optimization
Pareto Set Learning for Expensive Multi-Objective Optimization
Xi Lin
Zhiyuan Yang
Xiao-Yan Zhang
Qingfu Zhang
90
62
0
16 Oct 2022
Dimensionality Reduction and Prioritized Exploration for Policy Search
Dimensionality Reduction and Prioritized Exploration for Policy Search
Marius Memmel
Puze Liu
Davide Tateo
Jan Peters
122
4
0
09 Mar 2022
Megaverse: Simulating Embodied Agents at One Million Experiences per Second
Megaverse: Simulating Embodied Agents at One Million Experiences per Second
Aleksei Petrenko
Erik Wijmans
Brennan Shacklett
V. Koltun
LM&RoVGen
88
24
0
17 Jul 2021
Recent Theoretical Advances in Non-Convex Optimization
Recent Theoretical Advances in Non-Convex Optimization
Marina Danilova
Pavel Dvurechensky
Alexander Gasnikov
Eduard A. Gorbunov
Sergey Guminov
Dmitry Kamzolov
Innokentiy Shibaev
129
79
0
11 Dec 2020
AdaDGS: An adaptive black-box optimization method with a nonlocal directional Gaussian smoothing gradient
AdaDGS: An adaptive black-box optimization method with a nonlocal directional Gaussian smoothing gradient
Hoang Tran
Guannan Zhang
58
8
0
03 Nov 2020
MLE-guided parameter search for task loss minimization in neural sequence modeling
MLE-guided parameter search for task loss minimization in neural sequence modeling
Sean Welleck
Kyunghyun Cho
65
10
0
04 Jun 2020