Projekter pr. år
Abstract
We propose sparse approximation weighted regression (SPARROW), a method for local estimation of the regression function that uses sparse approximation with a dictionary of measurements. SPARROW estimates the regression function at a point with a linear combination of a few regressands selected by a sparse approximation of the point in terms of the regressors. We show SPARROW can be considered a variant of \(k\)-nearest neighbors regression (\(k\)-NNR), and more generally, local polynomial kernel regression. Unlike \(k\)-NNR, however, SPARROW can adapt the number of regressors to use based on the sparse approximation process. Our experimental results show the locally constant form of SPARROW performs competitively.
Originalsprog | Engelsk |
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Tidsskrift | Proceedings of the European Signal Processing Conference |
Vol/bind | 2012 |
Sider (fra-til) | 674-678 |
Antal sider | 5 |
ISSN | 2076-1465 |
Status | Udgivet - 2012 |
Begivenhed | EUSIPCO2012 - Bucharest, Rumænien Varighed: 27 aug. 2012 → … |
Konference
Konference | EUSIPCO2012 |
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Land/Område | Rumænien |
By | Bucharest |
Periode | 27/08/2012 → … |
Fingeraftryk
Dyk ned i forskningsemnerne om 'Regression with Sparse Approximations of Data'. Sammen danner de et unikt fingeraftryk.Projekter
- 1 Igangværende
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Greedy Sparse Approximation and the Automatic Description of Audio and Music Data
Sturm, B. L.
Technology and Production Independent Postdoc Center for Independent Research
01/01/2012 → …
Projekter: Projekt › Forskning