12 citations · 12 across the 1 of their papers we have counts for
3 papers
Perturbation Bounds for Procrustes, Classical Scaling, and Trilateration, with Applications to Manifold Learning
Ery Arias-Castro, Adel Javanmard, Bruno Pelletier
One of the common tasks in unsupervised learning is dimensionality reduction, where the goal is to find meaningful low-dimensional structures hidden in high-dimensional data. Somet…
On the Estimation of Latent Distances Using Graph Distances
Ery Arias-Castro, Antoine Channarond, Bruno Pelletier +1
We are given the adjacency matrix of a geometric graph and the task of recovering the latent positions. We study one of the most popular approaches which consists in using the grap…
On the convergence of maximum variance unfolding
Ery Arias-Castro, Bruno Pelletier
Maximum Variance Unfolding is one of the main methods for (nonlinear) dimensionality reduction. We study its large sample limit, providing specific rates of convergence under stand…