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05/30/2023
Clip21: Error Feedback for Gradient Clipping
Motivated by the increasing popularity and importance of large-scale tra...
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05/29/2023
Partially Personalized Federated Learning: Breaking the Curse of Data Heterogeneity
We present a partially personalized formulation of Federated Learning (F...
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10/31/2022
Adaptive Compression for Communication-Efficient Distributed Training
We propose Adaptive Compressed Gradient Descent (AdaCGD) - a novel optim...
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06/07/2022
Distributed Newton-Type Methods with Communication Compression and Bernoulli Aggregation
Despite their high computation and communication costs, Newton-type meth...
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11/02/2021
Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning
Recent advances in distributed optimization have shown that Newton-type ...
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06/05/2021
FedNL: Making Newton-Type Methods Applicable to Federated Learning
Inspired by recent work of Islamov et al (2021), we propose a family of ...
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02/14/2021