Hard thresholding pursuit algorithms: Number of iterations
نویسندگان
چکیده
منابع مشابه
Hard Thresholding Pursuit Algorithms: Number of Iterations
The Hard Thresholding Pursuit algorithm for sparse recovery is revisited using a new theoretical analysis. The main result states that all sparse vectors can be exactly recovered from compressive linear measurements in a number of iterations at most proportional to the sparsity level as soon as the measurement matrix obeys a certain restricted isometry condition. The recovery is also robust to ...
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The Hard Thresholding Pursuit (HTP) is a class of truncated gradient descent methods for finding sparse solutions of l0-constrained loss minimization problems. The HTP-style methods have been shown to have strong approximation guarantee and impressive numerical performance in high dimensional statistical learning applications. However, the current theoretical treatment of these methods has trad...
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We introduce a new iterative algorithm to find sparse solutions of underdetermined linear systems. The algorithm, a simple combination of the Iterative Hard Thresholding algorithm and of the Compressive Sampling Matching Pursuit or Subspace Pursuit algorithms, is called Hard Thresholding Pursuit. We study its general convergence, and notice in particular that only a finite number of iterations ...
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ژورنال
عنوان ژورنال: Applied and Computational Harmonic Analysis
سال: 2016
ISSN: 1063-5203
DOI: 10.1016/j.acha.2016.03.002