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arXiv · 1303.5259

Efficient Sparseness-Enforcing Projections

Markus Thom·Günther Palm
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Abstract

We propose a linear time and constant space algorithm for computing Euclidean projections onto sets on which a normalized sparseness measure attains a constant value. These non-convex target sets can be characterized as intersections of a simplex and a hypersphere. Some previous methods required the vector to be projected to be sorted, resulting in at least quasilinear time complexity and linear space complexity. We improve on this by adaptation of a linear time algorithm for projecting onto simplexes. In conclusion, we propose an efficient algorithm for computing the product of the gradient of the projection with an arbitrary vector.

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Markus Thom, Günther Palm. 2013-03-21. Efficient Sparseness-Enforcing Projections. https://arxiv.org/abs/1303.5259

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