We held our next tinyML Talks webcast. Ranjitha Prasad from IIIT Delhi presented Unsupervised Federated Learning on September 14, 2023.
Modern day applications such as autonomous vehicles, IoT, smart grids, etc., generate massive amounts of data at the edge. Federated Learning (FL) enables machine learning without having to transfer data from edge devices to any untrusted third party. A fundamental challenge in federated supervised learning is ensuring that data at the edge is annotated. This talk gives a general overview of federated learning with specific focuss on federated learning techniques that utilise the unannotated data at the edge for learning a global model.
Dr. Ranjitha Prasad obtained her Ph.D. from Indian Institute of Science in 2015. Her experience is in the general areas of signal processing, Bayesian statistics, and more recently, machine learning and deep neural networks. She has been a postdoctoral researcher at Nanyang Technological University and National University of Singapore, Singapore, and a scientist at TCS Innovation Labs, Delhi. Her current research interests are Causal Inference, explainable AI and federated learning.
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