Adaptive Incremental Provenance Analysis for Trustworthy Federated Learning

Yao, A; Dong, C; Pal, S; Jiang, Frank; Wang, H; Li, R; Feng, W; Liu, L; Gu, Z

Adaptive Incremental Provenance Analysis for Trustworthy Federated Learning

https://hdl.handle.net/10779/DRO/DU:30670898

conference contribution

posted on 2025-11-21, 00:29 authored by A Yao, C Dong, S Pal, Frank JiangFrank Jiang, H Wang, R Li, W Feng, L Liu, Z Gu

Adaptive Incremental Provenance Analysis for Trustworthy Federated Learning

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DOI - Is version of https://doi.org/10.1007/978-981-95-3456-2_30

Location

Kyoto, Japan

Open access

No

Language

eng

Volume

16198

Pagination

431-445

Start date

2025-10-22

End date

2025-10-24

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9789819534555

Title of proceedings

ADMA 2025 : Proceedings of the 21st International Conference on Advanced Data Mining and Applications

Event

Advanced Data Mining and Applications. Conference (2025 : 21st : Kyoto, Japan)

Publisher

Springer Nature

Series

Lecture Notes in Computer Science

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Adaptive Incremental Provenance Analysis for Trustworthy Federated Learning

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