Capture Global Feature Statistics for One-Shot Federated Learning Article Swipe
Zhenzhen Guan
,
Zhou Yucan
,
Xiaoyan Gu
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1609/aaai.v39i16.33862
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1609/aaai.v39i16.33862
Traditional Federated Learning (FL) necessitates numerous rounds of communication between the server and clients, posing significant challenges including high communication costs, connection drop risks and susceptibility to privacy attacks. One-shot FL has become a compelling learning paradigm to overcome above drawbacks by enabling the training of a global server model via a single communication round. However, existing one-shot FL methods suffer from expensive computation cost on the server or clients and cannot deal with non-IID (Independent and Identically Distributed) data stably and effectively. To address these challenges, this paper proposes FedCGS, a novel Federated learning algorithm that Capture Global feature Statistics leveraging pre-trained models. With global feature statistics, we achieve training-free and heterogeneity-resistant one-shot FL. Furthermore, we expand its application to personalization scenario, where clients only need execute one extra communication round with server to download global statistics. Extensive experimental results demonstrate the effectiveness of our methods across diverse data-heterogeneity settings.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1609/aaai.v39i16.33862
- https://ojs.aaai.org/index.php/AAAI/article/download/33862/36017
- OA Status
- diamond
- Cited By
- 2
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4409364349
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4409364349Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1609/aaai.v39i16.33862Digital Object Identifier
- Title
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Capture Global Feature Statistics for One-Shot Federated LearningWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-04-11Full publication date if available
- Authors
-
Zhenzhen Guan, Zhou Yucan, Xiaoyan GuList of authors in order
- Landing page
-
https://doi.org/10.1609/aaai.v39i16.33862Publisher landing page
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https://ojs.aaai.org/index.php/AAAI/article/download/33862/36017Direct link to full text PDF
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YesWhether a free full text is available
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-
diamondOpen access status per OpenAlex
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https://ojs.aaai.org/index.php/AAAI/article/download/33862/36017Direct OA link when available
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Feature (linguistics), Shot (pellet), Computer science, Artificial intelligence, Summary statistics, Statistics, Pattern recognition (psychology), Mathematics, Organic chemistry, Philosophy, Linguistics, ChemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
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2025: 2Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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