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Trustworthy federated learning = fir...

International Workshop on Trustworthy Federated Learning (2022 :)

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Trustworthy federated learning = first International Workshop, FL 2022, held in conjunction with IJCAI 2022, Vienna, Austria, July 23, 2022 : revised selected papers /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Trustworthy federated learning/ edited by Randy Goebel ... [et al.].
其他題名:	first International Workshop, FL 2022, held in conjunction with IJCAI 2022, Vienna, Austria, July 23, 2022 : revised selected papers /
其他題名:	FL 2022
其他作者:	Goebel, Randy.
團體作者:	International Workshop on Trustworthy Federated Learning
出版者:	Cham :Springer International Publishing : : 2023.,
面頁冊數:	x, 159 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Machine learning - Congresses. -
電子資源:	https://doi.org/10.1007/978-3-031-28996-5
ISBN:	9783031289965

Trustworthy federated learning = first International Workshop, FL 2022, held in conjunction with IJCAI 2022, Vienna, Austria, July 23, 2022 : revised selected papers /
Trustworthy federated learningfirst International Workshop, FL 2022, held in conjunction with IJCAI 2022, Vienna, Austria, July 23, 2022 : revised selected papers /[electronic resource] :FL 2022edited by Randy Goebel ... [et al.]. - Cham :Springer International Publishing :2023. - x, 159 p. :ill., digital ;24 cm. - Lecture notes in computer science,134481611-3349 ;. - Lecture notes in computer science ;13448..

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.

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.

ISBN: 9783031289965

Standard No.: 10.1007/978-3-031-28996-5doiSubjects--Topical Terms:

576368
Machine learning
--Congresses.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

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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