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» Algorithms for Large, Sparse Network Alignment Problems
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ICASSP
2011
IEEE
12 years 11 months ago
TLS-FOCUSS for sparse recovery with perturbed dictionary
In this paper, we propose a new algorithm, TLS-FOCUSS, for sparse recovery for large underdetermined linear systems, based on total least square (TLS) method and FOCUSS(FOCal Unde...
Xuebing Han, Hao Zhang, Huadong Meng
BMCBI
2005
158views more  BMCBI 2005»
13 years 7 months ago
Automated generation of heuristics for biological sequence comparison
Background: Exhaustive methods of sequence alignment are accurate but slow, whereas heuristic approaches run quickly, but their complexity makes them more difficult to implement. ...
Guy St. C. Slater, Ewan Birney
SIAMIS
2011
13 years 2 months ago
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
Matthias W. Seeger, Hannes Nickisch
CPHYSICS
2007
222views more  CPHYSICS 2007»
13 years 7 months ago
JADAMILU: a software code for computing selected eigenvalues of large sparse symmetric matrices
A new software code for computing selected eigenvalues and associated eigenvectors of a real symmetric matrix is described. The eigenvalues are either the smallest or those closes...
Matthias Bollhöfer, Yvan Notay
ECML
2007
Springer
14 years 1 months ago
Principal Component Analysis for Large Scale Problems with Lots of Missing Values
Abstract. Principal component analysis (PCA) is a well-known classical data analysis technique. There are a number of algorithms for solving the problem, some scaling better than o...
Tapani Raiko, Alexander Ilin, Juha Karhunen