50 citations · 250 across the 16 of their papers we have counts for
4 papers · 1 filter
Manifold learning with arbitrary norms
Joe Kileel, Amit Moscovich, Nathan Zelesko +1
Manifold learning methods play a prominent role in nonlinear dimensionality reduction and other tasks involving high-dimensional data sets with low intrinsic dimensionality. Many o…
Wasserstein K-Means for Clustering Tomographic Projections
Rohan Rao, Amit Moscovich, Amit Singer
Motivated by the 2D class averaging problem in single-particle cryo-electron microscopy (cryo-EM), we present a k-means algorithm based on a rotationally-invariant Wasserstein metr…
Product Manifold Learning
Sharon Zhang, Amit Moscovich, Amit Singer
We consider problems of dimensionality reduction and learning data representations for continuous spaces with two or more independent degrees of freedom. Such problems occur, for e…
Fast calculation of p-values for one-sided Kolmogorov-Smirnov type statistics
Amit Moscovich
A novel method for computing exact p-values of one-sided statistics from the Kolmogorov-Smirnov family is presented. It covers the Higher Criticism statistic, one-sided weighted Ko…