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cs.LG2025
Delayed Momentum Aggregation: Communication-efficient Byzantine-robust Federated Learning with Partial Participation
Kaoru Otsuka, Yuki Takezawa, Makoto Yamada
Partial participation is essential for communication-efficient federated learning at scale, yet existing Byzantine-robust methods typically assume full client participation. In the…
stat.ML2025
Any-stepsize Gradient Descent for Separable Data under Fenchel-Young Losses
Han Bao, Shinsaku Sakaue, Yuki Takezawa
The gradient descent (GD) has been one of the most common optimizer in machine learning. In particular, the loss landscape of a neural network is typically sharpened during the ini…