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NIPS
2008
14 years 11 months ago
Sparse Signal Recovery Using Markov Random Fields
Compressive Sensing (CS) combines sampling and compression into a single subNyquist linear measurement process for sparse and compressible signals. In this paper, we extend the th...
Volkan Cevher, Marco F. Duarte, Chinmay Hegde, Ric...
ICML
2010
IEEE
14 years 10 months ago
A DC Programming Approach for Sparse Eigenvalue Problem
We investigate the sparse eigenvalue problem which arises in various fields such as machine learning and statistics. Unlike standard approaches relying on approximation of the l0n...
Mamadou Thiao, Pham Dinh Tao, Le Thi Hoai An
CORR
2010
Springer
253views Education» more  CORR 2010»
14 years 10 months ago
Fast Inference in Sparse Coding Algorithms with Applications to Object Recognition
Adaptive sparse coding methods learn a possibly overcomplete set of basis functions, such that natural image patches can be reconstructed by linearly combining a small subset of t...
Koray Kavukcuoglu, Marc'Aurelio Ranzato, Yann LeCu...
CORR
2007
Springer
81views Education» more  CORR 2007»
14 years 10 months ago
Faster exon assembly by sparse spliced alignment
Assembling a gene from candidate exons is an important problem in computational biology. Among the most successful approaches to this problem is spliced alignment, proposed by Gelf...
Alexandre Tiskin
NN
2010
Springer
189views Neural Networks» more  NN 2010»
14 years 4 months ago
Sparse kernel learning with LASSO and Bayesian inference algorithm
Kernelized LASSO (Least Absolute Selection and Shrinkage Operator) has been investigated in two separate recent papers (Gao et al., 2008) and (Wang et al., 2007). This paper is co...
Junbin Gao, Paul W. Kwan, Daming Shi