Publications associées à On the influence of momentum acceleration on online learning

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

On the influence of momentum acceleration on online learning

Graph Chatbot

Chattez avec Graph Search

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

On the Generalization of Stochastic Gradient Descent with Momentum

Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization

UNDERGRAD: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees

STORM+: Fully Adaptive SGD with Momentum for Nonconvex Optimization

Increasing Superstructure Optimization Capacity Through Self-Learning Surrogate Models

Tomographic reconstruction of the runaway distribution function in TCV using multispectral synchrotron images

Computational Inverse Design of Surface-based Inflatables

Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent

Momentum space CFT correlators for Hamiltonian truncation

Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization

On the Generalization of Stochastic Gradient Descent with Momentum

Increasing Superstructure Optimization Capacity Through Self-Learning Surrogate Models

UNDERGRAD: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees

Computational Inverse Design of Surface-based Inflatables

Momentum space CFT correlators for Hamiltonian truncation

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent

STORM+: Fully Adaptive SGD with Momentum for Nonconvex Optimization

Tomographic reconstruction of the runaway distribution function in TCV using multispectral synchrotron images