In this paper, we discuss methods to refine locally optimal solutions of sparse PCA. Starting from a local solution obtained by existing algorithms, these methods take advantage of convex relaxations of the sparse PCA problem to propose a refined solution that is still locally optimal but with a higher objective value. © 2010 Springer -Verlag Berlin Heidelberg.
CITATION STYLE
Journée, M., Bach, F., Absil, P. A., & Sepulchre, R. (2010). Refining sparse principal components. In Recent Advances in Optimization and its Applications in Engineering (pp. 165–171). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-12598-0_14
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