Basic Information
Geometric Data Processing and Analysis Is a Fast-growing Research Direction With Applications in a Broad Range of Fields. It Is Based On Classical Areas Such As Differential Geometry and Harmonic Analysis, While Current Applications Involve Contemporary Topics Such As Geometric Deep Learning, Dimensionality Reduction, and Signal Processing On Graphs. The Main Purpose of This Course Is to Introduce The Fundamental Theory of Geometric Data Analysis, With Special Emphasis Put On a Unified Perspective On Both Continuous and Discrete Analysis, As Well As The Emerging Relatd Applications. Learning Outcomes# at The End of The Course The Studetns Will Be Able To# 1. Define Fundamental Terms in Spectral Graph Theory and Differential Geometry. 2. Apply Geometric Analysis Techniques to High-dimensional Data. 3. Implement (in Matlab/python) Algorithms For Data Embedding And Dimensionality Reduction.
Faculty: Electrical and Computer Engineering
|Pre-Academic
Course with no extra credit
48865 - Selective Topics in Signal Processing 2