Trustworthy Federated Learning
Springer International Publishing (Verlag)
978-3-031-28995-8 (ISBN)
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.
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.
| Erscheinungsdatum | 30.03.2023 |
|---|---|
| Reihe/Serie | Lecture Notes in Artificial Intelligence | Lecture Notes in Computer Science |
| Zusatzinfo | X, 159 p. 53 illus., 49 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 272 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Schlagworte | Applications • Artificial Intelligence • Collaborative Learning • Distillation • Dropout • federated learning • natural gas load forecasting • Network Protocols • Network Security • non-IID • personalization • privacy preservation • privacy preserving • secure aggregation • Signal Processing • social recommendation • trustworthiness • vertical federated learning • World Wide Web |
| ISBN-10 | 3-031-28995-1 / 3031289951 |
| ISBN-13 | 978-3-031-28995-8 / 9783031289958 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
aus dem Bereich
