Study of an area of current interest in theoretical computer science. Topic varies from term to term. This course is a study of Behavior of Algorithms and covers an area of current interest in theoretical computer science. The topics vary from term to term. During this term, we discuss rigorous approaches to explaining the typical performance of algorithms with a focus on the following approaches: smoothed analysis, condition numbers/parametric analysis, and subclassing inputs.

This is a collection of notes for a one-semester course in linear algebra taught at San Jacinto College (Houston, Texas). The notes are suited for a first course in linear algebra taken by students who have completed one year of single-variable calculus. Unlike most traditional linear algebra textbooks, these notes begin with the ideas of vector spaces and linear functions (transformations). Since functions play a central role in calculus, this approach should seem more natural to students. Systems of linear equations and matrix theory are presented afterward as consequences of the preceding material. The result is an economical (only 175 pages) treatment of the main themes of linear algebra along with a few applications of the theory to geometry, economics, and cryptography.