Linear and Sublinear Algorithms for Graphlet Sampling

Explore a 33-minute lecture on graphlet sampling algorithms presented by Marco Bressan from the University of Milan at the Simons Institute. Delve into the problem of uniformly sampling a connected induced k-vertex subgraph from a simple graph G, where k ≥ 3. Examine both linear and sublinear preprocessing time algorithms for this challenge. Discover recent adaptations of these algorithms to semi-streaming and MPC (Massively Parallel Computation) settings. Gain insights into the field of extroverted sublinear algorithms and their applications in graph theory and computational complexity.