On the forward and backward algorithms of projection pursuit
نویسندگان
چکیده
منابع مشابه
A Forward-Backward Projection Algorithm for Approximating of the Zero of the Sum of Two Operators
In this paper, a forward-backward projection algorithm is considered for finding zero points of the sum of two operators in Hilbert spaces. The sequence generated by algorithm converges strongly to the zero point of the sum of an $alpha$-inverse strongly monotone operator and a maximal monotone operator. We apply the result for solving the variational inequality problem, fixed po...
متن کاملOn the Forward and Backward Algorithms of Projection Pursuit1 by Mu Zhu
This article provides a historic review of the forward and backward projection pursuit algorithms, previously thought to be equivalent, and points out an important difference between the two. In doing so, a small error in the original exploratory projection pursuit article by Friedman [J. Amer. Statist. Assoc. 82 (1987) 249–266] is corrected. The implication of the difference is briefly discuss...
متن کاملImprovement of Forward-Backward Pursuit Algorithm Based on Weak Selection
Forward-backward pursuit (FBP) algorithm is a novel two-stage greedy approach. However once its forward and backward steps were determined during iteration, it would make computing time increased and affected the reconstruction efficiency. This paper presents a algorithm called forward-backward pursuit algorithm based on weak selection (SWFBP) by introducing threshold strategy into FBP algorith...
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We propose the Forward-Backward Synergistic Acceleration Pursuit (FBSAP) algorithm in this paper. The FBSAP algorithm inherits the advantages of the Forward-Backward Pursuit (FBP) algorithm, which has high success rate of reconstruction and does not necessitate the sparsity level as a priori condition. Moreover, it solves the problem of FBP that the atom can be selected only by the fixed step s...
متن کاملILU and IUL factorizations obtained from forward and backward factored approximate inverse algorithms
In this paper, an efficient dropping criterion has been used to compute the IUL factorization obtained from Backward Factored APproximate INVerse (BFAPINV) and ILU factorization obtained from Forward Factored APproximate INVerse (FFAPINV) algorithms. We use different drop tolerance parameters to compute the preconditioners. To study the effect of such a dropping on the quality of the ILU ...
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ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 2004
ISSN: 0090-5364
DOI: 10.1214/aos/1079120135