Abstract: Federated learning (FL) is an innovative privacy-preserving machine learning paradigm that enables clients to train a global model without sharing their local data. However, the coexistence ...

Abstract: The growing Internet traffic urgently needs large-capacity and cost-effective optical transmissions. To maintain system performance under low-cost conditions, the silicon-based integrated ...

Objective: This study aimed to determine optimal sample sizes and the relationships between sample size and dataset-level characteristics over a variety of binary classification algorithms. Methods: A ...