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researcher

Ming Xiao Xie

2 papers here

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

author position
  • middle author2

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

fields
  • cs.LG2
ORCID 0000-0003-1088-1158

identity via Semantic Scholar / OpenAlex

most citedMulti-Center Federated Learning: Clients Clustering for Better Personalization

300 citations · 600 across the 2 of their papers we have counts for

collaborators
Showing cs.LGShow all

2 papers · 1 filter

cs.LG2021★ 300 cited

Multi-Center Federated Learning: Clients Clustering for Better Personalization

Guodong Long, Ming Xie, Tao Shen +4

Personalized decision-making can be implemented in a Federated learning (FL) framework that can collaboratively train a decision model by extracting knowledge across intelligent cl…

cs.LG2020★ 300 cited

Multi-Center Federated Learning: Clients Clustering for Better Personalization

Guodong Long, Ming Xie, Tao Shen +4

Federated learning has received great attention for its capability to train a large-scale model in a decentralized manner without needing to access user data directly. It helps pro…

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