YoVDO

Toward Optimal Semi-streaming Algorithm for (1+ε)-Approximate Maximum Matching

Offered By: Simons Institute via YouTube

Tags

Graph Theory Courses Computational Complexity Courses Approximation Algorithms Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore a 31-minute lecture on developing a deterministic algorithm for the (1+ε)-approximate maximum matching problem. Delve into Wen-Horng Sheu's research from UC Davis, presented at the Workshop on Local Algorithms (WoLA) at the Simons Institute. Learn about the significant improvement in semi-streaming pass complexity from O(ε^-19) to O(ε^-6), advancing towards resolving an open question in the field. Discover how this algorithm enhances round complexity for computing (1+ε)-approximate maximum matching in Massively Parallel Computation and CONGEST models. Examine the use of blossoms and alternating trees in data structure representation, simplifying correctness analysis by treating aspects as if operating on bipartite graphs. Gain insights into how this approach overcomes technical challenges present in previous work.

Syllabus

Toward Optimal Semi-streaming Algorithm for (1+ε)-approximate Maximum Matching


Taught by

Simons Institute

Related Courses

Approximation Algorithms Part I
École normale supérieure via Coursera
Approximation Algorithms Part II
École normale supérieure via Coursera
Shortest Paths Revisited, NP-Complete Problems and What To Do About Them
Stanford University via Coursera
Algorithm Design and Analysis
University of Pennsylvania via edX
Delivery Problem
University of California, San Diego via Coursera