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Apprentissage automatique

Publications associées (1 000)

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Byzantine Fault-Tolerance in Federated Local SGD Under 2f-Redundancy

Nirupam Gupta

In this article, we study the problem of Byzantine fault-tolerance in a federated optimization setting, where there is a group of agents communicating with a centralized coordinator. We allow up to

f

Byzantine-faulty agents, which may not follow a prescr ...

Piscataway2023

Apprentissage automatique

Graph Chatbot

Chattez avec Graph Search

Predicting party switching through machine learning and open data

Model agnostic methods meta-learn despite misspecifications

Learning Robust and Adaptive Representations: from Interactions, for Interactions

Class Specific Feature Disentanglement and Text Embeddings for Multi-label Generalized Zero Shot CXR Classification

Byzantine Fault-Tolerance in Federated Local SGD Under 2f-Redundancy

Enriching the Computational Toolbox for Organocatalysis

Stochastic adaptive resampling for the estimation of discrete choice models

Predicting Survey Response with Quotation-based Modeling: A Case Study on Favorability towards the United States

NMDA-driven dendritic modulation enables multitask representation learning in hierarchical sensory processing pathways

Mutation-Attention (MuAt): deep representation learning of somatic mutations for tumour typing and subtyping

Enriching the Computational Toolbox for Organocatalysis

Predicting Survey Response with Quotation-based Modeling: A Case Study on Favorability towards the United States

Class Specific Feature Disentanglement and Text Embeddings for Multi-label Generalized Zero Shot CXR Classification

Learning Robust and Adaptive Representations: from Interactions, for Interactions

Model agnostic methods meta-learn despite misspecifications

Predicting party switching through machine learning and open data

Byzantine Fault-Tolerance in Federated Local SGD Under 2f-Redundancy

Stochastic adaptive resampling for the estimation of discrete choice models

NMDA-driven dendritic modulation enables multitask representation learning in hierarchical sensory processing pathways

Mutation-Attention (MuAt): deep representation learning of somatic mutations for tumour typing and subtyping