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.mehr

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