Unsupervised Federated Learning for Edge Computing Applications

Explore a comprehensive tinyML talk that delves into the world of unsupervised federated learning, presented by Assistant Professor Ranjitha Prasad from IIIT Delhi. Learn how federated learning enables machine learning applications to function without transferring data from edge devices to untrusted third parties, particularly crucial for modern applications like autonomous vehicles, IoT, and smart grids. Discover solutions to the fundamental challenge of data annotation in federated supervised learning, with special emphasis on techniques that leverage unannotated edge data for global model development. Master the concepts of processing massive amounts of edge-generated data while maintaining privacy and efficiency in distributed learning systems.