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» Approximation schemes for clustering problems
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SDM
2011
SIAM
414views Data Mining» more  SDM 2011»
14 years 13 days ago
Clustered low rank approximation of graphs in information science applications
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
Berkant Savas, Inderjit S. Dhillon
SODA
1998
ACM
128views Algorithms» more  SODA 1998»
14 years 11 months ago
A Polynomial-Time Approximation Scheme for Weighted Planar Graph TSP
Given a planar graph on n nodes with costs weights on its edges, de ne the distance between nodes i and j as the length of the shortest path between i and j. Consider this as an i...
Sanjeev Arora, Michelangelo Grigni, David R. Karge...
DEXAW
2007
IEEE
135views Database» more  DEXAW 2007»
15 years 4 months ago
Unsupervised Learning of Manifolds via Linear Approximations
In this paper, we examine the application of manifold learning to the clustering problem. The method used is Locality Preserving Projections (LPP), which is chosen because of its ...
Hassan A. Kingravi, M. Emre Celebi, Pragya P. Raja...
MOC
2002
127views more  MOC 2002»
14 years 9 months ago
The dynamical behavior of the discontinuous Galerkin method and related difference schemes
We study the dynamical behavior of the discontinuous Galerkin finite element method for initial value problems in ordinary differential equations. We make two different assumptions...
Donald J. Estep, Andrew M. Stuart
IPL
1998
119views more  IPL 1998»
14 years 9 months ago
A 2.5-Factor Approximation Algorithm for the k-MST Problem
The k-MST problem requires finding that subset of at least k vertices of a given graph whose Minimum Spanning Tree has least weight amongst all subsets of at least k vertices. Th...
Sunil Arya, H. Ramesh