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CVPR
2004
IEEE
14 years 9 months ago
Joint Feature-Basis Subset Selection
We treat feature selection and basis selection in a unified framework by introducing the masking matrix. If one considers feature selection as finding a binary mask vector that de...
Shai Avidan
TSP
2008
102views more  TSP 2008»
13 years 7 months ago
Spatially Adaptive Estimation via Fitted Local Likelihood Techniques
Abstract--This paper offers a new technique for spatially adaptive estimation. The local likelihood is exploited for nonparametric modeling of observations and estimated signals. T...
Vladimir Katkovnik, Vladimir Spokoiny
BMCBI
2004
167views more  BMCBI 2004»
13 years 7 months ago
Feature selection for splice site prediction: A new method using EDA-based feature ranking
Background: The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Oth...
Yvan Saeys, Sven Degroeve, Dirk Aeyels, Pierre Rou...
ICCV
2003
IEEE
14 years 9 months ago
Regression based Bandwidth Selection for Segmentation using Parzen Windows
We consider the problem of segmentation of images that can be modelled as piecewise continuous signals having unknown, non-stationary statistics. We propose a solution to this pro...
Maneesh Kumar Singh, Narendra Ahuja
IJCNN
2008
IEEE
14 years 2 months ago
Sparse kernel density estimator using orthogonal regression based on D-Optimality experimental design
— A novel sparse kernel density estimator is derived based on a regression approach, which selects a very small subset of significant kernels by means of the D-optimality experi...
Sheng Chen, Xia Hong, Chris J. Harris