An Approach to Federated Learning of Explainable Fuzzy Regression Models-Reference-Cited by-同舟云学术

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An Approach to Federated Learning of Explainable Fuzzy Regression Models

Published:2022-07-18 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
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Author:

Corcuera Barcena Jose Luis¹,Ducange Pietro¹,Ercolani Alessio¹,Marcelloni Francesco¹,Renda Alessandro¹

Affiliation:

1. University of Pisa,Department of Information Engineering,Pisa,Italy,56122

Funder

European Commission

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9882530/9882539/09882881.pdf?arnumber=9882881

Reference23 articles.

1. Federated optimization: Distributed machine learning for on-device intelligence;konec??;arXiv preprint arXiv 1610 02984,2016

2. Horizontal federated learning of takagi-sugeno fuzzy rule-based models;zhu;IEEE T Fuzzy Syst,2021

3. Federated FCM: Clustering Under Privacy Requirements;pedrycz;IEEE T Fuzzy Syst,2021

4. A federated fuzzy c-means clustering algorithm;corcuera bárcena;Int’l Workshop on Fuzzy Logic and Applications 2021,2021

5. Design of adaptive Takagi–Sugeno–Kang fuzzy models

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4. Trustworthy AI in Heterogeneous Settings: Federated Learning of Explainable Classifiers;2024 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE);2024-06-30

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