Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

Testing Thresholds for High-Dimensional Sparse Random Geometric Graphs

Simons Institute via YouTube

Overview

Explore the intricacies of distinguishing Erdős-Rényi graphs from random geometric graphs in this 56-minute lecture by Siqi Liu from UC Berkeley. Delve into structural results that improve upon previous bounds and nearly resolve a conjecture by Bubeck, Ding, Eldan, and Rácz. Examine key proof ideas, including the analysis of the Belief Propagation algorithm and sharp estimates for sphere cap intersections using optimal transport maps and entropy-transport inequalities. Gain insights into statistical indistinguishability thresholds for various probability ranges and understand the implications of this joint work with Sidhanth Mohanty, Tselil Schramm, and Elizabeth Yang on high-dimensional sparse random geometric graphs.

Syllabus

Testing Thresholds for High-dimensional Sparse Random Geometric Graphs

Taught by

Simons Institute

Reviews

Start your review of Testing Thresholds for High-Dimensional Sparse Random Geometric Graphs

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.