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12/03/2022
GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning
Federated learning (FL) is an effective technique to directly involve ed...
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06/13/2022
Accelerating Federated Learning via Sampling Anchor Clients with Large Batches
Using large batches in recent federated learning studies has improved co...
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04/14/2022
Sign Bit is Enough: A Learning Synchronization Framework for Multi-hop All-reduce with Ultimate Compression
Traditional one-bit compressed stochastic gradient descent can not be di...
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12/17/2021
From Deterioration to Acceleration: A Calibration Approach to Rehabilitating Step Asynchronism in Federated Optimization
In the setting of federated optimization, where a global model is aggreg...
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11/04/2021