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Fast Candidate Poin...
Fast Candidate Points Selection in the LASSO Path
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- Panahi, Ashkan, 1986 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Viberg, Mats, 1961 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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(creator_code:org_t)
- 2012
- 2012
- Engelska.
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Ingår i: IEEE Signal Processing Letters. - 1070-9908 .- 1558-2361. ; 19:2, s. 79-82
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Abstract
Ämnesord
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- The LASSO sparse regression method has recently received attention in a variety of applications from image compression techniques to parameter estimation problems. This paper addresses the problem of regularization parameter selection in this method in a general case of complex-valued regressors and bases. Generally, this parameter controls the degree of sparsity or equivalently, the estimated model order. However, with the same sparsity/model order, the smallest regularization parameter is desired. We relate such points to the nonsmooth points in the path of LASSO solutions and give an analytical expression for them. Then, we introduce a numerically fast method of approximating the desired points by a recursive algorithm. The procedure decreases the necessary number of solutions of the LASSO problem dramatically, which is an important issue due to the polynomial computational cost of the convex optimization techniques. We illustrate our method in the context of DOA estimation.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)
Nyckelord
- stagewise regression
- Homotopy
- LASSO
- model
- linear regression
- regression
- LARS
Publikations- och innehållstyp
- art (ämneskategori)
- ref (ämneskategori)
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