Private Data Quality Assessment for Smart Cities

  • February 10, 2025
  • CDPG
  • 0 Comments

Adaptive Self-Distillation for Minimizing Client Drift in Heterogeneous Federated Learning Authors: M. Yashwanth, G. K. Nayak, A. Singh, Y. Simmhan, A. Chakraborty Federated Learning (FL) is a machine learning paradigm that enables clients to jointly train a global model by aggregating the locally trained models without sharing any local training data. In practice, there can often be substantial heterogeneity (e.g., …

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