A smoothed complexity landscape. (Image courtesy of Prof. Daniel Spielman.)
This course features lecture notes that summarize the topics discussed and analyzed in class, as well as MATLAB® code that is presented for better understanding of the course materials.
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.
Special software is required to use some of the files in this course: .m, .mat.