Tao Lin

RelaySum for Decentralized Deep Learning on Heterogeneous Data

2021 · arXiv (Cornell University)

In decentralized machine learning, workers compute model updates on their local data. Because the workers only communicate with few neighbors without central coordination, these updates propagate progressively over the network. This paradigm enables distributed training …

FedGuCci: Making Local Models More Connected in Landscape for Federated Learning

2024 · arXiv (Cornell University)

Federated learning (FL) involves multiple heterogeneous clients collaboratively training a global model via iterative local updates and model fusion. The generalization of FL's global model has a large gap compared with centralized training, which is …