A proximal point algorithm for sequential feature extraction applications

Details A proximal point algorithm for sequential feature extraction applications A proximal point algorithm for sequential feature extraction applications

2011-08-04

arxiv.org/abs/1108.0986v1

Mathematics

Optimization and Control

Scientific paper

We propose a proximal point algorithm to solve LAROS problem, that is the problem of finding a "large approximately rank-one submatrix". This LAROS problem is used to sequentially extract features in data. We also develop a new stopping criterion for the proximal point algorithm, which is based on the duality conditions of \eps-optimal solutions of the LAROS problem, with a theoretical guarantee. We test our algorithm with two image databases and show that we can use the LAROS problem to extract appropriate common features from these images.

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