
Robust Federated Learning: The Case of Affine Distribution Shifts
Federated learning is a distributed paradigm that aims at training model...
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FedPAQ: A CommunicationEfficient Federated Learning Method with Periodic Averaging and Quantization
Federated learning is a new distributed machine learning approach, where...
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Robust and CommunicationEfficient Collaborative Learning
We consider a decentralized learning problem, where a set of computing n...
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CodedReduce: A Fast and Robust Framework for Gradient Aggregation in Distributed Learning
We focus on the commonly used synchronous Gradient Descent paradigm for ...
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Quantized Decentralized Consensus Optimization
We consider the problem of decentralized consensus optimization, where t...
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Coded Computing for Distributed Graph Analytics
Many distributed graph computing systems have been developed recently fo...
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Amirhossein Reisizadeh
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