Trustworthy Federated Learning

First International Workshop, FL 2022, Held in Conjunction with IJCAI 2022, Vienna, Austria, July 23, 2022, Revised Selected Papers
Herausgegeben:Goebel, Randy; Yu, Han; Faltings, Boi; Fan, Lixin; Xiong, Zehui

• Broschiertes Buch

Produktbeschreibung

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.

Produktdetails

• Lecture Notes in Computer Science 13448
• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-031-28995-8
• 1st ed. 2023
• Seitenzahl: 172
• Erscheinungstermin: 29. März 2023
• Englisch
• Abmessung: 235mm x 155mm x 10mm
• Gewicht: 271g
• ISBN-13: 9783031289958
• ISBN-10: 3031289951
• Artikelnr.: 67488777

Inhaltsangabe

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.