Navigating Alignment for Non-identical Client Class Sets: A Label Name-Anchored Federated Learning Framework-Reference-Cited by-同舟云学术

Navigating Alignment for Non-identical Client Class Sets: A Label Name-Anchored Federated Learning Framework

Published:2023-08-04 Issue: Volume: Page:
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Container-title:Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Zhang Jiayun¹^ORCID,Zhang Xiyuan¹^ORCID,Zhang Xinyang²^ORCID,Hong Dezhi³^ORCID,Gupta Rajesh K.¹^ORCID,Shang Jingbo¹^ORCID

Affiliation:

1. University of California, San Diego, La Jolla, CA, USA

2. University of Illinois at Urbana-Champaign, Urbana, IL, USA

3. Amazon, Sunnyvale, CA, USA

Funder

NSF (National Science Foundation)

NIH (National Institutes of Health)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3580305.3599443

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4. Jacob Devlin , Ming-Wei Chang , Kenton Lee , and Kristina Toutanova . 2018 . BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv preprint arXiv:1810.04805 (2018). Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv preprint arXiv:1810.04805 (2018).

5. Expert-augmented machine learning

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