Publications associées à Extrapolation for Large-batch Training in Deep 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.

Square Attack: a query-efficient black-box adversarial attack via random search

Nicolas Henri Bernard Flammarion, Maksym Andriushchenko, Francesco Croce

We propose the Square Attack, a new score-based black-box

l_2

and

l_\infty

adversarial attack that does not rely on local gradient information and thus is not affected by gradient masking. The Square Attack is based on a randomized search scheme where ...

2020

Extrapolation for Large-batch Training in Deep Learning

Graph Chatbot

Chattez avec Graph Search

Byzantine Fault-Tolerant Distributed Machine Learning with Norm-Based Comparative Gradient Elimination

Implicit Bias of SGD for Diagonal Linear Networks: a Provable Benefit of Stochasticity

Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent

Second-Order Guarantees In Federated Learning

Deep Generative Models and Applications

Probabilistic Deep Learning on Spheres for Weather/Climate Applications

Square Attack: a query-efficient black-box adversarial attack via random search

Reducing Noise in GAN Training with Variance Reduced Extragradient

Local SGD Converges Fast and Communicates Little

Geometry of adversarial robustness of deep networks: methods and applications

Deep Generative Models and Applications

Byzantine Fault-Tolerant Distributed Machine Learning with Norm-Based Comparative Gradient Elimination

Probabilistic Deep Learning on Spheres for Weather/Climate Applications

Geometry of adversarial robustness of deep networks: methods and applications

Second-Order Guarantees In Federated Learning

Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent

Reducing Noise in GAN Training with Variance Reduced Extragradient

Square Attack: a query-efficient black-box adversarial attack via random search

Implicit Bias of SGD for Diagonal Linear Networks: a Provable Benefit of Stochasticity

Local SGD Converges Fast and Communicates Little