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» Parallelizing Feature Selection
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129
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PAMI
2006
206views more  PAMI 2006»
15 years 2 months ago
MILES: Multiple-Instance Learning via Embedded Instance Selection
Multiple-instance problems arise from the situations where training class labels are attached to sets of samples (named bags), instead of individual samples within each bag (called...
Yixin Chen, Jinbo Bi, James Ze Wang
106
Voted
CGF
2005
109views more  CGF 2005»
15 years 2 months ago
GeoFilter: Geometric Selection of Mesh Filter Parameters
When designing a lowpass filter to eliminate noise in a triangle mesh, the cutoff frequency is typically chosen by a cumbersome trial-and-error process. Therefore, it is important...
ByungMoon Kim, Jarek Rossignac
146
Voted
ICANN
2009
Springer
15 years 14 days ago
Mining Rules for the Automatic Selection Process of Clustering Methods Applied to Cancer Gene Expression Data
Different algorithms have been proposed in the literature to cluster gene expression data, however there is no single algorithm that can be considered the best one independently on...
André C. A. Nascimento, Ricardo Bastos Cava...
155
Voted
DEXAW
2007
IEEE
157views Database» more  DEXAW 2007»
15 years 6 months ago
Dimensionality Reduction in a P2P System
Peers and data objects in the Hybrid Overlay Network (HON) are organized in a ndimensional feature space. As the dimensionality increases, peers and data objects become sparse and ...
Mouna Kacimi, Kokou Yétongnon
107
Voted
ICA
2004
Springer
15 years 8 months ago
A Model for Analyzing Dependencies Between Two ICA Features in Natural Images
Abstract. In this paper we examine how the activation of one independent component analysis (ICA) feature changes first and second order statistics of other independent components...
Mika Inki