Sparsest Cut: ARV Theorem

This lecture covers the proof of the Bourgain's ARV (Arora - Rao - Vazirani) Theorem, focusing on the finite set of points in a semi-metric space. The instructor demonstrates the uniform sampling and the key concepts behind the theorem, such as the distance between points and the concept of negative type. The lecture concludes with the application of the ARV algorithm to find the sparsest cut in a graph. Various Lemmas are introduced to support the main theorem, emphasizing the importance of the metric properties and the existence of specific sets in the context of the theorem.