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Efficient Basis Pursuit DeNoising via Active Sets and Homotopy
Suely P. Oliveira, E. Stewart
295 - 301
10.3233/978-1-61499-927-0-295
Frontiers in Artificial Intelligence and Applications
Volume 309: Fuzzy Systems and Data Mining IV
Abstract

The Basis Pursuit DeNoising problem is a variant of the well-known lasso method for obtaining sparse least-squares approximations, which can be represented as the minimization problem min β½‖Aβ−y‖22+λ‖β‖1. In this paper the problem is treated as a parametric quadratic program with parameter λ≥0. By this technique, very large scale problems can be essentially solved exactly for a range of values of λ, as long as the number of non-zero components of β is small to modest.

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