2 papers
cs.LG2024
Faster Convergence of Local SGD for Over-Parameterized Models
Tiancheng Qin, S. Rasoul Etesami, César A. Uribe
Modern machine learning architectures are often highly expressive. They are usually over-parameterized and can interpolate the data by driving the empirical loss close to zero. We…
cs.LG2024
Adaptive Federated Learning with Auto-Tuned Clients
Junhyung Lyle Kim, Mohammad Taha Toghani, César A. Uribe +1
Federated learning (FL) is a distributed machine learning framework where the global model of a central server is trained via multiple collaborative steps by participating clients…