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» Null space conditions and thresholds for rank minimization
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COMPUTING
2004
88views more  COMPUTING 2004»
13 years 8 months ago
Spline Curve Approximation and Design by Optimal Control Over the Knots
In [1] Optimal Control methods over re-parametrization for curve and surface design were introduced. The advantage of Optimal Control over Global Minimization such as in [17] is t...
Rony Goldenthal, Michel Bercovier
SIGMOD
2007
ACM
181views Database» more  SIGMOD 2007»
14 years 8 months ago
Progressive and selective merge: computing top-k with ad-hoc ranking functions
The family of threshold algorithm (i.e., TA) has been widely studied for efficiently computing top-k queries. TA uses a sort-merge framework that assumes data lists are pre-sorted...
Dong Xin, Jiawei Han, Kevin Chen-Chuan Chang
SIAMJO
2011
12 years 11 months ago
Rank-Sparsity Incoherence for Matrix Decomposition
Suppose we are given a matrix that is formed by adding an unknown sparse matrix to an unknown low-rank matrix. Our goal is to decompose the given matrix into its sparse and low-ran...
Venkat Chandrasekaran, Sujay Sanghavi, Pablo A. Pa...
SDM
2008
SIAM
125views Data Mining» more  SDM 2008»
13 years 10 months ago
Mining and Ranking Generators of Sequential Patterns
Sequential pattern mining first proposed by Agrawal and Srikant has received intensive research due to its wide range applicability in many real-life domains. Various improvements...
David Lo, Siau-Cheng Khoo, Jinyan Li
CORR
2011
Springer
194views Education» more  CORR 2011»
13 years 10 days ago
Sparse approximation property and stable recovery of sparse signals from noisy measurements
—In this paper, we introduce a sparse approximation property of order s for a measurement matrix A: xs 2 ≤ D Ax 2 + β σs(x) √ s for all x, where xs is the best s-sparse app...
Qiyu Sun