Master Production-Ready Machine Learning, Step by Step
Learn AI, Data Science & Business — Earn Certificates That Get You Hired
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 a 24-minute lecture on approximating maximum matching in graph theory. Delve into the latest research findings presented by Mohammad Roghani from Stanford University at the Simons Institute. Learn about the challenges in estimating the size of maximum matching and the recent breakthrough by Bhattacharya, Kiss, and Saranurak. Discover how their algorithm achieves an estimate within ε n of the optimal solution in subquadratic time. Examine the gap between existing lower bounds and the potential for faster algorithms. Uncover the speaker's contribution in closing this gap, proving that the BKS algorithm is near-optimal. Gain insights into the time complexity requirements for estimating maximum matching size within specific error bounds in the adjacency list model.
Syllabus
Approximating Maximum Matching Requires Almost Quadratic Time
Taught by
Simons Institute