Selected Topics in Signal Processing and Machine Learning Over Networks

(3 Credit Hours) · Undergraduate

This course introduces selected topics in signal processing and machine learning over networks. Topics presented include basic regression and classification techniques, and their implementations for cases when data is spread over several devices. Additionally, graph-based signal processing suitable for analyzing data arising from large-scale interactive systems will be covered. Time permitting, we will also present an overview on geometric deep learning techniques and their application in real-world scenarios (like the Netflix problem). The course will blend basic theory with computer projects; in particular, projects illustrating the presented concepts will follow a series of lectures along with possible seminar presentations. There will be a final project. This course is open to Undergraduate seniors and graduate students.