
Computing Steiner Trees using Graph Neural Networks
Graph neural networks have been successful in many learning problems and...
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On Matrix Factorizations in Subspace Clustering
This article explores subspace clustering algorithms using CUR decomposi...
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Modewise Tensor Decompositions: Multidimensional Generalizations of CUR Decompositions
Low rank tensor approximation is a fundamental tool in modern machine le...
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On additive spanners in weighted graphs with local error
An additive +β spanner of a graph G is a subgraph which preserves distan...
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Multilevel Weighted Additive Spanners
Given a graph G = (V,E), a subgraph H is an additive +β spanner if _H(u,...
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Robust CUR Decomposition: Theory and Imaging Applications
This paper considers the use of Robust PCA in a CUR decomposition framew...
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Rapid Robust Principal Component Analysis: CUR Accelerated Inexact Low Rank Estimation
Robust principal component analysis (RPCA) is a widely used tool for dim...
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Stability of Sampling for CUR Decompositions
This article studies how to form CUR decompositions of lowrank matrices...
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Graph Spanners: A Tutorial Review
This tutorial review provides a guiding reference to researchers who wan...
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Perturbations of CUR Decompositions
The CUR decomposition is a factorization of a lowrank matrix obtained b...
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Perspectives on CUR Decompositions
This note discusses an interesting matrix factorization called the CUR D...
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A General Framework for Multilevel Subsetwise Graph Sparsifiers
Given an undirected weighted graph $G(V,E)$, a subsetwise sparsifier ove...
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Approximation algorithms and an integer program for multilevel graph spanners
Given a weighted graph G(V,E) and t > 1, a subgraph H is a tspanner of...
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CUR Decompositions, Approximations, and Perturbations
This article discusses a useful tool in dimensionality reduction and low...
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CUR Decompositions, Similarity Matrices, and Subspace Clustering
A general framework for solving the subspace clustering problem using th...
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Keaton Hamm
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