Publications associées à STORM+: Fully Adaptive SGD with Momentum for Nonconvex Optimization

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

Nicolas Henri Bernard Flammarion, Hristo Georgiev Papazov, Scott William Pesme

In this work, we investigate the effect of momentum on the optimisation trajectory of gradient descent. We leverage a continuous-time approach in the analysis of momentum gradient descent with step size

\gamma

and momentum parameter

\beta

that allows u ...

2024

STORM+: Fully Adaptive SGD with Momentum for Nonconvex Optimization

Graph Chatbot

Chattez avec Graph Search

Residual-based attention in physics-informed neural networks

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

On the Generalization of Stochastic Gradient Descent with Momentum

Universal and adaptive methods for robust stochastic optimization

Contextual Stochastic Bilevel Optimization

Phenomenological theory of variational quantum ground-state preparation

Fast Adversarial Training With Adaptive Step Size

The statistical complexity of early-stopped mirror descent

Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks

ADAGRAD Avoids Saddle Points

Residual-based attention in physics-informed neural networks

Contextual Stochastic Bilevel Optimization

Universal and adaptive methods for robust stochastic optimization

Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks

ADAGRAD Avoids Saddle Points

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

Phenomenological theory of variational quantum ground-state preparation

The statistical complexity of early-stopped mirror descent

On the Generalization of Stochastic Gradient Descent with Momentum

Fast Adversarial Training With Adaptive Step Size