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Sparse eigen methods by D.C. programming
Bharath K. Sriperumbudur
, David A. Torres
, Gert R.G. Lanckriet
Statistics
Research output
:
Contribution to conference
›
Paper
›
peer-review
61
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Scopus citations
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Keyphrases
Cardinality Constraint
100%
Eigen
100%
Sparse Principal Component Analysis
100%
Tight
50%
Nonconvex
50%
Machine Learning
50%
Convex Programming
50%
L1-norm
50%
Dimensionality Reduction
50%
Eigenvalue Problem
50%
Problem Analysis
50%
Relevant Genes
50%
Generalized Eigenvalue Problem
50%
Variational Formulation
50%
Norm Approximation
50%
Locally Convex
50%
Difference of Convex Functions
50%
Negative Log-likelihood
50%
Student-t Distribution
50%
Computer Science
Approximation (Algorithm)
100%
Component Analysis
100%
Principal Components
100%
Cardinality
100%
Eigenvalue
100%
Dimensionality Reduction
50%
Convex Function
50%
Learning System
50%
Machine Learning
50%
Variational Formulation
50%
Mathematics
Variance
100%
Cardinality
100%
Eigenvalue Problem
100%
Principal Component Analysis
100%
Dimensionality Reduction
50%
Convex Programming
50%
Convex Function
50%
Variational Formulation
50%
Log Likelihood
50%
Locally Convex
50%