EE 378B – Inference, Estimation, and Information Processing

Tools from modern high-dimensional probability and statistics, with applications to data science, machine learning, and algorithms. Special attention will be given to problems that arise from the analysis of matrix, graph and tensor data.

Mathematical tools:

• Concentration inequalities

• Random matrix theory

• Gaussian comparison

Algorithmic tools:

• Spectral methods

• SDP relaxations

• Message passing

Problems

• Clustering;

• Matrix completion

• Graph localization

• Dimensionality reduction and manifold learning

Class Times and Locations

• Mon-Wed, 4:00-5:20pm