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researcher

Mete Ozay

1 paper here

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

author position
  • last author1

Across the 1 of 1 paper where every author was matched, so the position is known.

fields
  • cs.LG1
same name
  • Mete Ozay — 8 papers, h 11
  • Mete Ozay — 2 papers, h 4
  • Mete Ozay — 1 paper, h 4
  • Mete Ozay — 1 paper
  • Mete Ozay — 1 paper, h 1
  • Mete Ozay — 1 paper, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedPrototype Guided Federated Learning of Visual Feature Representations

25 citations · 25 across the 1 of their papers we have counts for

collaborators

1 paper

cs.LG2021★ 25 cited

Prototype Guided Federated Learning of Visual Feature Representations

Umberto Michieli, Mete Ozay

Federated Learning (FL) is a framework which enables distributed model training using a large corpus of decentralized training data. Existing methods aggregate models disregarding…

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