Course Schedule and Catalog

Long Title: NEURAL NETWORKS AND INFORMATION THEORY I

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: Review of major Artificial Neural Network paradigms. Analytical discussion of supervised and unsupervised learning. Emphasis on state-of-the-art Hebbian (biologically most plausible) learning paradigms and their relation to information theoretical methods. Applications to data analysis such as pattern recognition, clustering, classification, blind source separation, non-linear PCA. Cross-list: COMP 502, ELEC 502.