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Learning-Rate-Free Learning by D-Adaptation

Learning-Rate-Free Learning by D-Adaptation

18 January 2023
Aaron Defazio
Konstantin Mishchenko
ArXivPDFHTML

Papers citing "Learning-Rate-Free Learning by D-Adaptation"

15 / 65 papers shown
Title
Adaptive Federated Learning with Auto-Tuned Clients
Adaptive Federated Learning with Auto-Tuned Clients
J. Kim
Taha Toghani
César A. Uribe
Anastasios Kyrillidis
FedML
48
6
0
19 Jun 2023
Towards Stability of Autoregressive Neural Operators
Towards Stability of Autoregressive Neural Operators
Michael McCabe
P. Harrington
Shashank Subramanian
Jed Brown
AI4CE
44
17
0
18 Jun 2023
Prodigy: An Expeditiously Adaptive Parameter-Free Learner
Prodigy: An Expeditiously Adaptive Parameter-Free Learner
Konstantin Mishchenko
Aaron Defazio
ODL
33
56
0
09 Jun 2023
Simple and Controllable Music Generation
Simple and Controllable Music Generation
Jade Copet
Felix Kreuk
Itai Gat
Tal Remez
David Kant
Gabriel Synnaeve
Yossi Adi
Alexandre Défossez
MGen
42
340
0
08 Jun 2023
Mechanic: A Learning Rate Tuner
Mechanic: A Learning Rate Tuner
Ashok Cutkosky
Aaron Defazio
Harsh Mehta
OffRL
19
15
0
31 May 2023
Parameter-free projected gradient descent
Parameter-free projected gradient descent
Evgenii Chzhen
Christophe Giraud
Gilles Stoltz
22
4
0
31 May 2023
DoWG Unleashed: An Efficient Universal Parameter-Free Gradient Descent
  Method
DoWG Unleashed: An Efficient Universal Parameter-Free Gradient Descent Method
Ahmed Khaled
Konstantin Mishchenko
Chi Jin
ODL
27
22
0
25 May 2023
Stochastic Ratios Tracking Algorithm for Large Scale Machine Learning
  Problems
Stochastic Ratios Tracking Algorithm for Large Scale Machine Learning Problems
Shigeng Sun
Yuchen Xie
18
3
0
17 May 2023
MoMo: Momentum Models for Adaptive Learning Rates
MoMo: Momentum Models for Adaptive Learning Rates
Fabian Schaipp
Ruben Ohana
Michael Eickenberg
Aaron Defazio
Robert Mansel Gower
32
10
0
12 May 2023
Random Function Descent
Random Function Descent
Felix Benning
L. Döring
21
0
0
02 May 2023
Stochastic Nonsmooth Convex Optimization with Heavy-Tailed Noises:
  High-Probability Bound, In-Expectation Rate and Initial Distance Adaptation
Stochastic Nonsmooth Convex Optimization with Heavy-Tailed Noises: High-Probability Bound, In-Expectation Rate and Initial Distance Adaptation
Zijian Liu
Zhengyuan Zhou
27
10
0
22 Mar 2023
DoG is SGD's Best Friend: A Parameter-Free Dynamic Step Size Schedule
DoG is SGD's Best Friend: A Parameter-Free Dynamic Step Size Schedule
Maor Ivgi
Oliver Hinder
Y. Carmon
ODL
26
56
0
08 Feb 2023
Aggregated Residual Transformations for Deep Neural Networks
Aggregated Residual Transformations for Deep Neural Networks
Saining Xie
Ross B. Girshick
Piotr Dollár
Z. Tu
Kaiming He
297
10,220
0
16 Nov 2016
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
L. V. D. van der Maaten
Kilian Q. Weinberger
PINN
3DV
291
36,371
0
25 Aug 2016
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
296
39,198
0
01 Sep 2014
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