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Kitsuya Azuma

2 papers hereh-index 11 citations2 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2

Across the 2 of 2 papers where every author was matched, so the position is known.

fields
  • cs.LG2

identity via Semantic Scholar / OpenAlex

most citedSoft-Label Caching and Sharpening for Communication-Efficient Federated Distillation

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2026

BlazeFL: Fast and Deterministic Federated Learning Simulation

Kitsuya Azuma, Takayuki Nishio

Federated learning (FL) research increasingly relies on single-node simulations with hundreds or thousands of virtual clients, making both efficiency and reproducibility essential.…

cs.LG2026★ 1 cited

Soft-Label Caching and Sharpening for Communication-Efficient Federated Distillation

Kitsuya Azuma, Takayuki Nishio, Yuichi Kitagawa +2

Federated Learning (FL) enables collaborative model training across decentralized clients, enhancing privacy by keeping data local. Yet conventional FL, relying on frequent paramet…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.