1.

Record Nr.

UNISA996517751703316

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

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023

ISBN

9783031289965

9783031289958

Edizione

[1st ed. 2023.]

Descrizione fisica

1 online resource (168 pages) : illustrations

Collana

Lecture Notes in Artificial Intelligence, , 2945-9141 ; ; 13448

Disciplina

006.3

Soggetti

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

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

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.