On using graph distances to estimate Euclidean and related distances

Abstract: Graph distances have proven quite useful in machine learning/statistics, particularly in the estimation of Euclidean or geodesic distances. The talk will include a partial review of the literature, and then present more recent developments on the estimation of curvature-constrained distances on a surface, as well as on the estimation of Euclidean distances based on an unweighted and noisy neighborhood graph.

statistics theory

Audience: researchers in the topic

Stochastics and Statistics Seminar Series

Series comments: Description: MIT seminar on statistics, data science and related topics