Federated Repair of Deep Neural Networks

Author:

Li Calsi Davide1ORCID,Laurent Thomas2ORCID,Arcaini Paolo3ORCID,Ishikawa Fuyuki3ORCID

Affiliation:

1. Technische Universitat Muenchen, Munich, Germany

2. JSPS @ National Institute of Informatics, Tokyo, Japan

3. National Institute of Informatics, Tokyo, Japan

Funder

JST-Mirai Program

Publisher

ACM

Reference32 articles.

1. 2023. Repository for the paper "Arachne: Search-Based Repair of Deep Neural Networks". https://github.com/coinse/arachne/tree/v2.

2. bashtage. 2023. Implementation of ChaCha cipher-based PRNG. https://bashtage.github.io/randomgen/bit_generators/chacha.html.

3. Lukas Budach, Moritz Feuerpfeil, Nina Ihde, Andrea Nathansen, Nele Sina Noack, Hendrik Patzlaff, Hazar Harmouch, and Felix Naumann. 2022. The Effects of Data Quality on ML-Model Performance. CoRR abs/2207.14529 (2022). arXiv:2207.14529

4. Understanding Distributed Poisoning Attack in Federated Learning

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