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.

Linear and sublinear algorithms for graphlet sampling