Publication

Byzantine tolerant gradient descent for distributed machine learning with adversaries

Publications associées (32)

Graph Chatbot

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.

Connectez-vous pour utiliser Chat avec Graph Search

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Scott William Pesme

In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

2

-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

EPFL2024

Byzantine tolerant gradient descent for distributed machine learning with adversaries

Graph Chatbot

Chattez avec Graph Search

Understanding generalization and robustness in modern deep learning

Residual-based attention in physics-informed neural networks

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Robust machine learning for neuroscientific inference

Random matrix methods for high-dimensional machine learning models

Topics in statistical physics of high-dimensional machine learning

On the Generalization of Stochastic Gradient Descent with Momentum

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Revisiting Character-level Adversarial Attacks for Language Models

Understanding generalization and robustness in modern deep learning

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Residual-based attention in physics-informed neural networks

Robust machine learning for neuroscientific inference

Random matrix methods for high-dimensional machine learning models

Topics in statistical physics of high-dimensional machine learning

On the Generalization of Stochastic Gradient Descent with Momentum

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Revisiting Character-level Adversarial Attacks for Language Models