Random Graph Matching with Improved Noise Robustness

Random Graph Matching with Improved Noise Robustness

Explore a 44-minute lecture on graph matching and network alignment, focusing on a new algorithm for exact matching of correlated Erdos-Renyi graphs. Delve into this fundamental computational problem that has applications in computer vision and biology. Learn about the process of finding a bijection between vertex sets of two given graphs to maximally align their edges. Discover the improved noise robustness of the presented algorithm, based on joint work with Cheng Mao and Mark Rudelson. Gain insights into this cutting-edge research presented by Konstantin Tikhomirov at the Hausdorff Center for Mathematics.