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VeLO: Training Versatile Learned Optimizers by Scaling Up

VeLO: Training Versatile Learned Optimizers by Scaling Up

17 November 2022
Luke Metz
James Harrison
C. Freeman
Amil Merchant
Lucas Beyer
James Bradbury
Naman Agrawal
Ben Poole
Igor Mordatch
Adam Roberts
Jascha Narain Sohl-Dickstein
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Papers citing "VeLO: Training Versatile Learned Optimizers by Scaling Up"

50 / 51 papers shown
Title
Recursive Self-Similarity in Deep Weight Spaces of Neural Architectures: A Fractal and Coarse Geometry Perspective
Recursive Self-Similarity in Deep Weight Spaces of Neural Architectures: A Fractal and Coarse Geometry Perspective
A. Moharil
I. Kumara
Damian Tamburri
Majid Mohammadi
Willem-jan Van Den Heuvel
60
0
0
18 Mar 2025
Make Optimization Once and for All with Fine-grained Guidance
Mingjia Shi
Ruihan Lin
Xuxi Chen
Yuhao Zhou
Zezhen Ding
...
Tong Wang
Kai Wang
Zhangyang Wang
J. Zhang
Tianlong Chen
53
1
0
14 Mar 2025
Learning Versatile Optimizers on a Compute Diet
Learning Versatile Optimizers on a Compute Diet
A. Moudgil
Boris Knyazev
Guillaume Lajoie
Eugene Belilovsky
138
0
0
22 Jan 2025
Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning
Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning
Richa Upadhyay
Ronald Phlypo
Rajkumar Saini
Marcus Liwicki
35
0
0
21 Jan 2025
Applications of fractional calculus in learned optimization
Applications of fractional calculus in learned optimization
Teodor Alexandru Szente
James Harrison
M. Zanfir
C. Sminchisescu
66
0
0
22 Nov 2024
Learning on LoRAs: GL-Equivariant Processing of Low-Rank Weight Spaces
  for Large Finetuned Models
Learning on LoRAs: GL-Equivariant Processing of Low-Rank Weight Spaces for Large Finetuned Models
Theo Putterman
Derek Lim
Yoav Gelberg
Stefanie Jegelka
Haggai Maron
AI4CE
43
5
0
05 Oct 2024
Narrowing the Focus: Learned Optimizers for Pretrained Models
Narrowing the Focus: Learned Optimizers for Pretrained Models
Gus Kristiansen
Mark Sandler
A. Zhmoginov
Nolan Miller
Anirudh Goyal
Jihwan Lee
Max Vladymyrov
34
1
0
17 Aug 2024
Learning to Explore for Stochastic Gradient MCMC
Learning to Explore for Stochastic Gradient MCMC
Seunghyun Kim
Seohyeon Jung
Seonghyeon Kim
Juho Lee
BDL
48
1
0
17 Aug 2024
Learning to Learn without Forgetting using Attention
Learning to Learn without Forgetting using Attention
Anna Vettoruzzo
Joaquin Vanschoren
Mohamed-Rafik Bouguelia
Thorsteinn Rögnvaldsson
CLL
39
2
0
06 Aug 2024
Can Learned Optimization Make Reinforcement Learning Less Difficult?
Can Learned Optimization Make Reinforcement Learning Less Difficult?
Alexander David Goldie
Chris Xiaoxuan Lu
Matthew Jackson
Shimon Whiteson
Jakob N. Foerster
40
3
0
09 Jul 2024
Discovering Minimal Reinforcement Learning Environments
Discovering Minimal Reinforcement Learning Environments
Jarek Liesen
Chris Xiaoxuan Lu
Andrei Lupu
Jakob N. Foerster
Henning Sprekeler
R. T. Lange
OffRL
46
3
0
18 Jun 2024
Discovering Preference Optimization Algorithms with and for Large
  Language Models
Discovering Preference Optimization Algorithms with and for Large Language Models
Chris Xiaoxuan Lu
Samuel Holt
Claudio Fanconi
Alex J. Chan
Jakob Foerster
M. Schaar
R. T. Lange
OffRL
32
15
0
12 Jun 2024
$μ$LO: Compute-Efficient Meta-Generalization of Learned Optimizers
μμμLO: Compute-Efficient Meta-Generalization of Learned Optimizers
Benjamin Thérien
Charles-Étienne Joseph
Boris Knyazev
Edouard Oyallon
Irina Rish
Eugene Belilovsky
AI4CE
38
1
0
31 May 2024
Implicit Neural Image Field for Biological Microscopy Image Compression
Implicit Neural Image Field for Biological Microscopy Image Compression
Gaole Dai
Cheng-Ching Tseng
Qingpo Wuwu
Rongyu Zhang
Shaokang Wang
...
Yu Zhou
A. A. Tuz
Matthias Gunzer
Jianxu Chen
Shanghang Zhang
25
1
0
29 May 2024
Text-to-Model: Text-Conditioned Neural Network Diffusion for Train-Once-for-All Personalization
Text-to-Model: Text-Conditioned Neural Network Diffusion for Train-Once-for-All Personalization
Zexi Li
Lingzhi Gao
Chao Wu
AI4CE
DiffM
55
3
0
23 May 2024
Graph Neural Networks for Learning Equivariant Representations of Neural
  Networks
Graph Neural Networks for Learning Equivariant Representations of Neural Networks
Miltiadis Kofinas
Boris Knyazev
Yan Zhang
Yunlu Chen
Gertjan J. Burghouts
E. Gavves
Cees G. M. Snoek
David W. Zhang
44
29
0
18 Mar 2024
Dynamic Memory Based Adaptive Optimization
Dynamic Memory Based Adaptive Optimization
Balázs Szegedy
Domonkos Czifra
Péter Korösi-Szabó
ODL
27
0
0
23 Feb 2024
Discovering Temporally-Aware Reinforcement Learning Algorithms
Discovering Temporally-Aware Reinforcement Learning Algorithms
Matthew Jackson
Chris Xiaoxuan Lu
Louis Kirsch
R. T. Lange
Shimon Whiteson
Jakob N. Foerster
19
18
0
08 Feb 2024
Universal Neural Functionals
Universal Neural Functionals
Allan Zhou
Chelsea Finn
James Harrison
27
12
0
07 Feb 2024
AutoFT: Learning an Objective for Robust Fine-Tuning
AutoFT: Learning an Objective for Robust Fine-Tuning
Caroline Choi
Yoonho Lee
Annie S. Chen
Allan Zhou
Aditi Raghunathan
Chelsea Finn
OOD
44
0
0
18 Jan 2024
MADA: Meta-Adaptive Optimizers through hyper-gradient Descent
MADA: Meta-Adaptive Optimizers through hyper-gradient Descent
Kaan Ozkara
Can Karakus
Parameswaran Raman
Mingyi Hong
Shoham Sabach
B. Kveton
V. Cevher
21
2
0
17 Jan 2024
Graph Metanetworks for Processing Diverse Neural Architectures
Graph Metanetworks for Processing Diverse Neural Architectures
Derek Lim
Haggai Maron
Marc T. Law
Jonathan Lorraine
James Lucas
AI4CE
31
30
0
07 Dec 2023
Can We Learn Communication-Efficient Optimizers?
Can We Learn Communication-Efficient Optimizers?
Charles-Étienne Joseph
Benjamin Thérien
A. Moudgil
Boris Knyazev
Eugene Belilovsky
29
1
0
02 Dec 2023
Generalisable Agents for Neural Network Optimisation
Generalisable Agents for Neural Network Optimisation
Kale-ab Tessera
C. Tilbury
Sasha Abramowitz
Ruan de Kock
Omayma Mahjoub
Benjamin Rosman
Sara Hooker
Arnu Pretorius
AI4CE
20
0
0
30 Nov 2023
A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors
A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors
Olivier Laurent
Emanuel Aldea
Gianni Franchi
BDL
UQCV
20
5
0
12 Oct 2023
Making Scalable Meta Learning Practical
Making Scalable Meta Learning Practical
Sang Keun Choe
Sanket Vaibhav Mehta
Hwijeen Ahn
W. Neiswanger
Pengtao Xie
Emma Strubell
Eric P. Xing
47
14
0
09 Oct 2023
A Machine Learning-oriented Survey on Tiny Machine Learning
A Machine Learning-oriented Survey on Tiny Machine Learning
Luigi Capogrosso
Federico Cunico
D. Cheng
Franco Fummi
Marco Cristani
SyDa
MU
29
33
0
21 Sep 2023
Learning to Warm-Start Fixed-Point Optimization Algorithms
Learning to Warm-Start Fixed-Point Optimization Algorithms
Rajiv Sambharya
Georgina Hall
Brandon Amos
Bartolomeo Stellato
30
12
0
14 Sep 2023
Hyperparameters in Reinforcement Learning and How To Tune Them
Hyperparameters in Reinforcement Learning and How To Tune Them
Theresa Eimer
Marius Lindauer
Roberta Raileanu
OffRL
27
34
0
02 Jun 2023
HUB: Guiding Learned Optimizers with Continuous Prompt Tuning
Gaole Dai
Wei Yu Wu
Ziyu Wang
Jie Fu
Shanghang Zhang
Tiejun Huang
AIFin
14
0
0
26 May 2023
Neural Functional Transformers
Neural Functional Transformers
Allan Zhou
Kaien Yang
Yiding Jiang
Kaylee Burns
Winnie Xu
Samuel Sokota
J. Zico Kolter
Chelsea Finn
16
31
0
22 May 2023
Graph Reinforcement Learning for Network Control via Bi-Level
  Optimization
Graph Reinforcement Learning for Network Control via Bi-Level Optimization
Daniele Gammelli
James Harrison
Kaidi Yang
Marco Pavone
Filipe Rodrigues
Francisco Câmara Pereira
AI4CE
28
6
0
16 May 2023
Discovering Attention-Based Genetic Algorithms via Meta-Black-Box
  Optimization
Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimization
R. T. Lange
Tom Schaul
Yutian Chen
Chris Xiaoxuan Lu
Tom Zahavy
Valentin Dalibard
Sebastian Flennerhag
24
34
0
08 Apr 2023
Mathematical Challenges in Deep Learning
Mathematical Challenges in Deep Learning
V. Nia
Guojun Zhang
I. Kobyzev
Michael R. Metel
Xinlin Li
...
S. Hemati
M. Asgharian
Linglong Kong
Wulong Liu
Boxing Chen
AI4CE
VLM
37
1
0
24 Mar 2023
Permutation Equivariant Neural Functionals
Permutation Equivariant Neural Functionals
Allan Zhou
Kaien Yang
Kaylee Burns
Adriano Cardace
Yiding Jiang
Samuel Sokota
J. Zico Kolter
Chelsea Finn
25
47
0
27 Feb 2023
MONGOOSE: Path-wise Smooth Bayesian Optimisation via Meta-learning
MONGOOSE: Path-wise Smooth Bayesian Optimisation via Meta-learning
Adam X. Yang
Laurence Aitchison
Henry B. Moss
29
4
0
22 Feb 2023
Symbolic Discovery of Optimization Algorithms
Symbolic Discovery of Optimization Algorithms
Xiangning Chen
Chen Liang
Da Huang
Esteban Real
Kaiyuan Wang
...
Xuanyi Dong
Thang Luong
Cho-Jui Hsieh
Yifeng Lu
Quoc V. Le
55
350
0
13 Feb 2023
Learning to Optimize for Reinforcement Learning
Learning to Optimize for Reinforcement Learning
Qingfeng Lan
Rupam Mahmood
Shuicheng Yan
Zhongwen Xu
OffRL
24
6
0
03 Feb 2023
Mnemosyne: Learning to Train Transformers with Transformers
Mnemosyne: Learning to Train Transformers with Transformers
Deepali Jain
K. Choromanski
Kumar Avinava Dubey
Sumeet Singh
Vikas Sindhwani
Tingnan Zhang
Jie Tan
OffRL
33
9
0
02 Feb 2023
A Nonstochastic Control Approach to Optimization
A Nonstochastic Control Approach to Optimization
Xinyi Chen
Elad Hazan
47
5
0
19 Jan 2023
Federated Automatic Differentiation
Federated Automatic Differentiation
Keith Rush
Zachary B. Charles
Zachary Garrett
FedML
34
1
0
18 Jan 2023
A Closer Look at Learned Optimization: Stability, Robustness, and
  Inductive Biases
A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases
James Harrison
Luke Metz
Jascha Narain Sohl-Dickstein
44
22
0
22 Sep 2022
Meta Optimal Transport
Meta Optimal Transport
Brandon Amos
Samuel N. Cohen
Giulia Luise
I. Redko
OT
22
22
0
10 Jun 2022
Tutorial on amortized optimization
Tutorial on amortized optimization
Brandon Amos
OffRL
75
43
0
01 Feb 2022
A Simple Guard for Learned Optimizers
A Simple Guard for Learned Optimizers
Isabeau Prémont-Schwarz
Jaroslav Vítkru
Jan Feyereisl
49
7
0
28 Jan 2022
Primer: Searching for Efficient Transformers for Language Modeling
Primer: Searching for Efficient Transformers for Language Modeling
David R. So
Wojciech Mañke
Hanxiao Liu
Zihang Dai
Noam M. Shazeer
Quoc V. Le
VLM
85
152
0
17 Sep 2021
MLP-Mixer: An all-MLP Architecture for Vision
MLP-Mixer: An all-MLP Architecture for Vision
Ilya O. Tolstikhin
N. Houlsby
Alexander Kolesnikov
Lucas Beyer
Xiaohua Zhai
...
Andreas Steiner
Daniel Keysers
Jakob Uszkoreit
Mario Lucic
Alexey Dosovitskiy
271
2,603
0
04 May 2021
Training Learned Optimizers with Randomly Initialized Learned Optimizers
Training Learned Optimizers with Randomly Initialized Learned Optimizers
Luke Metz
C. Freeman
Niru Maheswaranathan
Jascha Narain Sohl-Dickstein
41
12
0
14 Jan 2021
On the distance between two neural networks and the stability of
  learning
On the distance between two neural networks and the stability of learning
Jeremy Bernstein
Arash Vahdat
Yisong Yue
Ming-Yu Liu
ODL
195
57
0
09 Feb 2020
CAD2RL: Real Single-Image Flight without a Single Real Image
CAD2RL: Real Single-Image Flight without a Single Real Image
Fereshteh Sadeghi
Sergey Levine
SSL
226
809
0
13 Nov 2016
12
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