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goebel randy (curatore); yu han (curatore); faltings boi (curatore); fan lixin (curatore); xiong zehui (curatore) - trustworthy federated learning

Trustworthy Federated Learning First International Workshop, FL 2022, Held in Conjunction with IJCAI 2022, Vienna, Austria, July 23, 2022, Revised Selected Papers

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Dettagli

Genere:Libro
Lingua: Inglese
Editore:

Springer

Pubblicazione: 03/2023
Edizione: 1st ed. 2023





Trama

This book constitutes the refereed proceedings of the First International Workshop, FL 2022, Held in Conjunction with IJCAI 2022, held in Vienna, Austria, during July 23-25, 2022. 
The 11 full papers presented in this book were carefully reviewed and selected from 12 submissions. They are organized in three topical sections: answer set programming; adaptive expert models for personalization in federated learning and privacy-preserving federated cross-domain social recommendation.






Sommario

Adaptive Expert Models for Personalization in Federated Learning.- Federated Learning with GAN-based Data Synthesis for Non-iid Clients.- Practical and Secure Federated Recommendation with Personalized Mask.- A General Theory for Client Sampling in Federated Learning.- Decentralized adaptive clustering of deep nets is beneficial for client collaboration.- Sketch to Skip and Select: Communication Efficient Federated Learning using Locality Sensitive Hashing.- Fast Server Learning Rate Tuning for Coded Federated Dropout.- FedAUXfdp: Differentially Private One-Shot Federated Distillation.- Secure forward aggregation for vertical federated neural network.- Two-phased Federated Learning with Clustering and Personalization for Natural Gas Load Forecasting.- Privacy-Preserving Federated Cross-Domain Social Recommendation.










Altre Informazioni

ISBN:

9783031289958

Condizione: Nuovo
Collana: Lecture Notes in Computer Science
Dimensioni: 235 x 155 mm
Formato: Brossura
Illustration Notes:X, 159 p. 53 illus., 49 illus. in color.
Pagine Arabe: 159
Pagine Romane: x


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