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Recent Progress on Sublinear Time Algorithms for Maximum Matching - Lower Bounds

Simons Institute via YouTube

Overview

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Explore recent advancements in sublinear time algorithms for maximum matching, focusing on lower bounds, in this 47-minute lecture by Soheil Behnezhad from Northeastern University. Delve into a novel technique based on correlation decay that establishes super-linear lower bounds for estimating maximum matching size when the desired approximation exceeds 2/3. Gain insights into the challenges of designing algorithms that surpass linear-time performance, particularly in the context of dynamic graphs and algorithm design. Examine the implications of joint research with Mohammad Roghani and Aviad Rubinstein, as presented at the Simons Institute. Learn how these findings contribute to the ongoing quest for more efficient algorithmic solutions in graph theory and computational complexity.

Syllabus

Recent Progress on Sublinear Time Algorithms for Maximum Matching: Lower Bounds

Taught by

Simons Institute

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