Data Heterogeneity In Federated Learning
Federated learning has emerged as a revolutionary approach to machine learning, allowing multiple devices or institutions to collaboratively train models without sharing raw data. This decentralized approach is particularly useful in scenarios where privacy, security, or data ownership are critical concerns, such as healthcare, finance, and mobile applications. However, one of the key challenges in … Read more