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Gradient boosting

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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

Gradient boosting

Graph Chatbot

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Knowledge Distillation for 6D Pose Estimation by Aligning Distributions of Local Predictions

Model agnostic methods meta-learn despite misspecifications

Spatially adaptive machine learning models for predicting water quality in Hong Kong

Byzantine Machine Learning: A Primer

Cross-resolution Face Recognition via Identity-Preserving Network and Knowledge Distillation

The statistical complexity of early-stopped mirror descent

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

Fixing the problems of deep neural networks will require better training data and learning algorithms

Computationally Efficient Reinforcement Learning: Targeted Exploration leveraging Simple Rules

Subtleties in the trainability of quantum machine learning models

Model agnostic methods meta-learn despite misspecifications

Spatially adaptive machine learning models for predicting water quality in Hong Kong

Knowledge Distillation for 6D Pose Estimation by Aligning Distributions of Local Predictions

Byzantine Machine Learning: A Primer

Cross-resolution Face Recognition via Identity-Preserving Network and Knowledge Distillation

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

The statistical complexity of early-stopped mirror descent

Computationally Efficient Reinforcement Learning: Targeted Exploration leveraging Simple Rules

Subtleties in the trainability of quantum machine learning models

Fixing the problems of deep neural networks will require better training data and learning algorithms