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MoMo: Momentum Models for Adaptive Learning Rates
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MoMo: Momentum Models for Adaptive Learning Rates

Fabian Schaipp
Ruben Ohana
Michael Eickenberg
Aaron Defazio
Robert Mansel Gower
ArXiv (abs)PDFHTML

Papers citing "MoMo: Momentum Models for Adaptive Learning Rates"

4 / 4 papers shown
Title
How far away are truly hyperparameter-free learning algorithms?
How far away are truly hyperparameter-free learning algorithms?
Priya Kasimbeg
Vincent Roulet
Naman Agarwal
Sourabh Medapati
Fabian Pedregosa
Atish Agarwala
George E. Dahl
24
0
0
29 May 2025
Stochastic Polyak Step-sizes and Momentum: Convergence Guarantees and Practical Performance
Stochastic Polyak Step-sizes and Momentum: Convergence Guarantees and Practical Performance
Dimitris Oikonomou
Nicolas Loizou
95
6
0
06 Jun 2024
Enhancing Policy Gradient with the Polyak Step-Size Adaption
Enhancing Policy Gradient with the Polyak Step-Size Adaption
Yunxiang Li
Rui Yuan
Chen Fan
Mark Schmidt
Samuel Horváth
Robert Mansel Gower
Martin Takávc
72
0
0
11 Apr 2024
Implicit Bias and Fast Convergence Rates for Self-attention
Implicit Bias and Fast Convergence Rates for Self-attention
Bhavya Vasudeva
Puneesh Deora
Christos Thrampoulidis
114
21
0
08 Feb 2024

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