Publications associées à AGGREGATHOR: Byzantine Machine Learning via Robust Gradient Aggregation

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.

Beyond One Third Byzantine Failures

Rachid Guerraoui, Anne-Marie Kermarrec, Cheng Wang

The Byzantine agreement problem requires a set of

n

processes to agree on a value sent by a transmitter, despite a subset of

b

processes behaving in an arbitrary, i.e. Byzantine, manner and sending corrupted messages to all processes in the system. It ...

2015

AGGREGATHOR: Byzantine Machine Learning via Robust Gradient Aggregation

Graph Chatbot

Chattez avec Graph Search

Provable Robustness of ReLU networks via Maximization of Linear Regions

Geometry of adversarial robustness of deep networks: methods and applications

Towards goal-driven deep neural network models to elucidate human arm proprioception

Novelty Detection in Convolutional Neural Networks Using Density Forests

Asynchronous Byzantine Machine Learning (the case of SGD)

Adaptive data augmentation for image classification

Beyond One Third Byzantine Failures

Models of 802.11 Multi-Hop Networks: Theoretical Insights and Experimental Validation

ImageNet performance correlates with pose estimation robustness and generalization on out-of-domain data

Novelty Detection in Convolutional Neural Networks Using Density Forests

Asynchronous Byzantine Machine Learning (the case of SGD)

Geometry of adversarial robustness of deep networks: methods and applications

Adaptive data augmentation for image classification

Models of 802.11 Multi-Hop Networks: Theoretical Insights and Experimental Validation

Towards goal-driven deep neural network models to elucidate human arm proprioception

Provable Robustness of ReLU networks via Maximization of Linear Regions

Beyond One Third Byzantine Failures

ImageNet performance correlates with pose estimation robustness and generalization on out-of-domain data