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» Structured Low Rank Approximation of a Bezout Matrix
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SDM
2011
SIAM
414views Data Mining» more  SDM 2011»
12 years 7 months 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
CORR
2011
Springer
168views Education» more  CORR 2011»
12 years 12 months ago
Optimal Column-Based Low-Rank Matrix Reconstruction
We prove that for any real-valued matrix X ∈ Rm×n , and positive integers r k, there is a subset of r columns of X such that projecting X onto their span gives a r+1 r−k+1 -a...
Venkatesan Guruswami, Ali Kemal Sinop
ICCAD
2001
IEEE
124views Hardware» more  ICCAD 2001»
14 years 1 months ago
Highly Accurate Fast Methods for Extraction and Sparsification of Substrate Coupling Based on Low-Rank Approximation
More aggressive design practices have created renewed interest in techniques for analyzing substrate coupling problems. Most previous work has focused primarily on faster techniqu...
Joe Kanapka, Jacob White
TKDE
2012
270views Formal Methods» more  TKDE 2012»
11 years 7 months ago
Low-Rank Kernel Matrix Factorization for Large-Scale Evolutionary Clustering
—Traditional clustering techniques are inapplicable to problems where the relationships between data points evolve over time. Not only is it important for the clustering algorith...
Lijun Wang, Manjeet Rege, Ming Dong, Yongsheng Din...
CORR
2011
Springer
157views Education» more  CORR 2011»
12 years 8 months ago
Large-Scale Convex Minimization with a Low-Rank Constraint
We address the problem of minimizing a convex function over the space of large matrices with low rank. While this optimization problem is hard in general, we propose an efficient...
Shai Shalev-Shwartz, Alon Gonen, Ohad Shamir