Convex Relaxations for Subset Selection
TITLE: Convex Relaxations for Subset Selection
AUTHORS: Francis Bach, Selin Damla Ahipasaoglu, Alexandre d'Aspremont
ABSTRACT: We use convex relaxation techniques to produce lower bounds on the optimal value of subset selection problems and generate good approximate solutions. We then explicitly bound the quality of these relaxations by studying the approximation ratio of sparse eigenvalue relaxations. Our results are used to improve the performance of branch-and-bound algorithms to produce exact solutions to subset selection problems.
STATUS: In preparation.
ArXiv PREPRINT: 1006.3601
PAPER: Relaxations for Subset Selection in pdf
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