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Learn2Hop: Learned Optimization on Rough Landscapes

Learn2Hop: Learned Optimization on Rough Landscapes

20 July 2021
Amil Merchant
Luke Metz
S. Schoenholz
E. D. Cubuk
ArXivPDFHTML

Papers citing "Learn2Hop: Learned Optimization on Rough Landscapes"

13 / 13 papers shown
Title
Learning Versatile Optimizers on a Compute Diet
Learning Versatile Optimizers on a Compute Diet
A. Moudgil
Boris Knyazev
Guillaume Lajoie
Eugene Belilovsky
147
0
0
22 Jan 2025
AdsorbDiff: Adsorbate Placement via Conditional Denoising Diffusion
AdsorbDiff: Adsorbate Placement via Conditional Denoising Diffusion
Adeesh Kolluru
John R. Kitchin
DiffM
47
4
0
07 May 2024
Learning to Generalize Provably in Learning to Optimize
Learning to Generalize Provably in Learning to Optimize
Junjie Yang
Tianlong Chen
Mingkang Zhu
Fengxiang He
Dacheng Tao
Yitao Liang
Zhangyang Wang
31
6
0
22 Feb 2023
StriderNET: A Graph Reinforcement Learning Approach to Optimize Atomic
  Structures on Rough Energy Landscapes
StriderNET: A Graph Reinforcement Learning Approach to Optimize Atomic Structures on Rough Energy Landscapes
Vaibhav Bihani
S. Manchanda
Srikanth Sastry
Sayan Ranu
N. M. A. Krishnan
GNN
OffRL
AI4CE
26
4
0
29 Jan 2023
evosax: JAX-based Evolution Strategies
evosax: JAX-based Evolution Strategies
R. T. Lange
30
54
0
08 Dec 2022
Transformer-Based Learned Optimization
Transformer-Based Learned Optimization
Erik Gartner
Luke Metz
Mykhaylo Andriluka
C. Freeman
C. Sminchisescu
18
11
0
02 Dec 2022
Discovering Evolution Strategies via Meta-Black-Box Optimization
Discovering Evolution Strategies via Meta-Black-Box Optimization
R. T. Lange
Tom Schaul
Yutian Chen
Tom Zahavy
Valenti Dallibard
Chris Xiaoxuan Lu
Satinder Singh
Sebastian Flennerhag
44
47
0
21 Nov 2022
VeLO: Training Versatile Learned Optimizers by Scaling Up
VeLO: Training Versatile Learned Optimizers by Scaling Up
Luke Metz
James Harrison
C. Freeman
Amil Merchant
Lucas Beyer
...
Naman Agrawal
Ben Poole
Igor Mordatch
Adam Roberts
Jascha Narain Sohl-Dickstein
29
60
0
17 Nov 2022
Practical tradeoffs between memory, compute, and performance in learned
  optimizers
Practical tradeoffs between memory, compute, and performance in learned optimizers
Luke Metz
C. Freeman
James Harrison
Niru Maheswaranathan
Jascha Narain Sohl-Dickstein
33
32
0
22 Mar 2022
Distributional Reinforcement Learning for Scheduling of Chemical
  Production Processes
Distributional Reinforcement Learning for Scheduling of Chemical Production Processes
M. Mowbray
Dongda Zhang
Ehecatl Antonio del Rio Chanona
OffRL
17
6
0
01 Mar 2022
Tutorial on amortized optimization
Tutorial on amortized optimization
Brandon Amos
OffRL
75
43
0
01 Feb 2022
Learning to Optimize: A Primer and A Benchmark
Learning to Optimize: A Primer and A Benchmark
Tianlong Chen
Xiaohan Chen
Wuyang Chen
Howard Heaton
Jialin Liu
Zhangyang Wang
W. Yin
38
225
0
23 Mar 2021
The Loss Surfaces of Multilayer Networks
The Loss Surfaces of Multilayer Networks
A. Choromańska
Mikael Henaff
Michaël Mathieu
Gerard Ben Arous
Yann LeCun
ODL
179
1,185
0
30 Nov 2014
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