Explore the Goemans-Williamson algorithm for rounding solutions to the Max-Cut Semidefinite Programming (SDP) problem in this graduate-level lecture from Carnegie Mellon University's "CS Theory Toolkit" course. Delve into efficient methods for finding graph cuts that are at least 0.878 times the maximum cut. Examine key concepts such as positive semidefinite matrices, unit vectors, and notation through examples and in-depth analysis. Gain insights into the approximability of Constraint Satisfaction Problems (CSPs) and the Algebraic Dichotomy Conjecture. Access additional resources, including slides and a relevant survey paper, to further enhance your understanding of this advanced topic in theoretical computer science.
Goemans-Williamson: Rounding the Max-Cut SDP - Lecture 20a of CS Theory Toolkit
Overview
Syllabus
Introduction
MaxCut SDP
Positive semidefinite matrix
Unit vectors
Notation
Example
Analysis
Taught by
Ryan O'Donnell
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