3 citations · 6 across the 15 of their papers we have counts for
4 papers · 1 filter
TALLOP: Joint Optimization of Local Training and Communication Compression for Time-Constrained Federated Learning
Honoka Anada, Yafei Ou, Shinya Takamaeda-Yamazaki
Minimizing the wall-clock time required to reach a target accuracy is crucial in federated learning (FL), where many applications require frequent model updates as data distributio…
TRIP-Shapley: Propagation-Aware Contribution Attribution Framework for Peer-to-Peer Federated Learning
Honoka Anada, Tatsuya Kaneko, Yafei Ou +1
Contribution attribution is a fundamental problem in federated learning (FL), yet it remains challenging in peer-to-peer FL (P2PFL), where participant influence propagates through…
PRIOT: Pruning-Based Integer-Only Transfer Learning for Embedded Systems
Honoka Anada, Sefutsu Ryu, Masayuki Usui +2
On-device transfer learning is crucial for adapting a common backbone model to the unique environment of each edge device. Tiny microcontrollers, such as the Raspberry Pi Pico, are…
MP-GELU Bayesian Neural Networks: Moment Propagation by GELU Nonlinearity
Yuki Hirayama, Sinya Takamaeda-Yamazaki
Bayesian neural networks (BNNs) have been an important framework in the study of uncertainty quantification. Deterministic variational inference, one of the inference methods, util…