ECE 566 - Computational Inference

Fall 2021

Computational InferenceECE566G68111OLC41400 - 1520 T R    Pierre Moulin

Official Description

Computational inference and machine learning have seen a surge of interest in the last 15 years, motivated by applications as diverse as computer vision, speech recognition, analysis of networks and distributed systems, big-data analytics, large-scale computer simulations, and indexing and searching of very large databases. This course introduces the mathematical and computational methods that enable such applications. Topics include computational methods for statistical inference, sparsity analysis, approximate inference and search, and fast optimization. Course Information: 4 graduate hours. No professional credit. Prerequisite: ECE 490, ECE 534.

Subject Area

  • General Sciences

Course Director