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

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.