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117
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JMLR
2010
130views more  JMLR 2010»
14 years 10 months ago
A Regularization Approach to Nonlinear Variable Selection
In this paper we consider a regularization approach to variable selection when the regression function depends nonlinearly on a few input variables. The proposed method is based o...
Lorenzo Rosasco, Matteo Santoro, Sofia Mosci, Ales...
147
Voted
ECCV
1992
Springer
15 years 7 months ago
Data and Model-Driven Selection using Color Regions
A key problem in model-based object recognition is selection, namely, the problem of determining which regions in the image are likely to come from a single object. In this paper w...
Tanveer Fathima Syeda-Mahmood
163
Voted
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
15 years 7 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
116
Voted
ATAL
2006
Springer
15 years 7 months ago
A context-aware approach for service selection using ontologies
Selecting the right parties to interact with is a fundamental problem in open and dynamic environments. The problem is exemplified when the number of interacting parties is high a...
Murat Sensoy, Pinar Yolum
138
Voted
CVPR
2004
IEEE
16 years 5 months ago
Scale Selection for Anisotropic Scale-Space: Application to Volumetric Tumor Characterization
A unified approach for treating the scale selection problem in the anisotropic scale-space is proposed. The anisotropic scale-space is a generalization of the classical isotropic ...
Kazunori Okada, Dorin Comaniciu, Arun Krishnan