Stuck in Tutorial Hell? Learn Backend Dev the Right Way
Get 20% off all career paths from fullstack to AI
Overview
AI, Data Science & Cloud Certificates from Google, IBM & Meta — 40% Off
One plan covers every Professional Certificate on Coursera. 40% off Coursera Plus Annual.
Unlock All Certificates
Explore the SDP relaxation technique for the Max-Cut problem in this graduate-level lecture from Carnegie Mellon University's "CS Theory Toolkit" course. Learn how to transform an exact quadratic program into a linear program with infinite constraints, and discover how this relaxation leads to a semidefinite program solvable by the Ellipsoid Algorithm. Delve into advanced topics in theoretical computer science, drawing from resources like "Geometric Algorithms and Combinatorial Optimization" and "Laplacian eigenvalues and the maximum cut problem." Taught by Professor Ryan O'Donnell, this 33-minute lecture covers key concepts including linear programming, the Ellipsoid Algorithm, and semidefinite programming, providing essential knowledge for research in theoretical computer science.
Syllabus
Intro
Linear Programming
Standard Linear Programming
Smart Idea
Ellipsoid Algorithm
Inequality
SDP
The LPE
Taught by
Ryan O'Donnell