16 citations · 30 across the 8 of their papers we have counts for
3 papers · 1 filter
ManiFeSt: Manifold-based Feature Selection for Small Data Sets
David Cohen, Tal Shnitzer, Yuval Kluger +1
In this paper, we present a new method for few-sample supervised feature selection (FS). Our method first learns the manifold of the feature space of each class using kernels captu…
Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets
Tal Shnitzer, Mikhail Yurochkin, Kristjan Greenewald +1
The need for efficiently comparing and representing datasets with unknown alignment spans various fields, from model analysis and comparison in machine learning to trend discovery…
Spatiotemporal Analysis Using Riemannian Composition of Diffusion Operators
Tal Shnitzer, Hau-Tieng Wu, Ronen Talmon
Multivariate time-series have become abundant in recent years, as many data-acquisition systems record information through multiple sensors simultaneously. In this paper, we assume…