The Nyström method is an effective tool to generate low-rank
approximati...
We introduce LOT Wassmap, a computationally feasible algorithm to uncove...
A sparsification of a given graph G is a sparser graph (typically a
subg...
We characterize some variations of pseudoskeleton (also called CUR)
deco...
Robust Principal Component Analysis (PCA) has received massive attention...
In this paper, we propose Wasserstein Isometric Mapping (Wassmap), a
par...
Graph neural networks have been successful in many learning problems and...
This article explores subspace clustering algorithms using CUR
decomposi...
Low rank tensor approximation is a fundamental tool in modern machine
le...
An additive +β spanner of a graph G is a subgraph which
preserves distan...
Given a graph G = (V,E), a subgraph H is an additive +β
spanner if _H(u,...
This paper considers the use of Robust PCA in a CUR decomposition framew...
Robust principal component analysis (RPCA) is a widely used tool for
dim...
This article studies how to form CUR decompositions of low-rank matrices...
This tutorial review provides a guiding reference to researchers who wan...
The CUR decomposition is a factorization of a low-rank matrix obtained b...
This note discusses an interesting matrix factorization called the CUR
D...
Given an undirected weighted graph $G(V,E)$, a subsetwise sparsifier ove...
Given a weighted graph G(V,E) and t > 1, a subgraph H is a
t--spanner of...
This article discusses a useful tool in dimensionality reduction and low...
A general framework for solving the subspace clustering problem using th...