Sparse eigen methods by D.C. programming

  title={Sparse eigen methods by D.C. programming},
  author={Bharath K. Sriperumbudur and David A. Torres and Gert R. G. Lanckriet},
Eigenvalue problems are rampant in machine learning and statistics and appear in the context of classification, dimensionality reduction, etc. In this paper, we consider a cardinality constrained variational formulation of generalized eigenvalue problem with sparse principal component analysis (PCA) as a special case. Using l1-norm approximation to the cardinality constraint, previous methods have proposed both convex and non-convex solutions to the sparse PCA problem. In contrast, we propose a… CONTINUE READING
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