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Titolo: |
Trustworthy Federated Learning [[electronic resource] ] : First International Workshop, FL 2022, Held in Conjunction with IJCAI 2022, Vienna, Austria, July 23, 2022, Revised Selected Papers / / edited by Randy Goebel, Han Yu, Boi Faltings, Lixin Fan, Zehui Xiong
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Pubblicazione: | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
Edizione: | 1st ed. 2023. |
Descrizione fisica: | 1 online resource (168 pages) : illustrations |
Disciplina: | 006.3 |
Soggetto topico: | Artificial intelligence |
Data protection | |
Social sciences—Data processing | |
Application software | |
Artificial Intelligence | |
Data and Information Security | |
Computer Application in Social and Behavioral Sciences | |
Computer and Information Systems Applications | |
Persona (resp. second.): | YuHan (Assistant Professor) |
GoebelRandy | |
FaltingsBoi | |
FanLixin (Scientist) | |
XiongZehui | |
Nota di bibliografia: | Includes bibliographical references and index. |
Nota di contenuto: | 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. |
Sommario/riassunto: | 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. |
Titolo autorizzato: | Trustworthy Federated Learning ![]() |
ISBN: | 9783031289965 |
9783031289958 | |
Formato: | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 996517751703316 |
Lo trovi qui: | Univ. di Salerno |
Opac: | Controlla la disponibilità qui |