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» Structured metric learning for high dimensional problems
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CAIP
2003
Springer
222views Image Analysis» more  CAIP 2003»
15 years 2 months ago
Learning Statistical Structure for Object Detection
Abstract. Many classes of images exhibit sparse structuring of statistical dependency. Each variable has strong statistical dependency with a small number of other variables and ne...
Henry Schneiderman
59
Voted
CVPR
2008
IEEE
15 years 11 months ago
Dimensionality reduction by unsupervised regression
We consider the problem of dimensionality reduction, where given high-dimensional data we want to estimate two mappings: from high to low dimension (dimensionality reduction) and f...
Miguel Á. Carreira-Perpiñán, ...
ALGORITHMICA
2004
74views more  ALGORITHMICA 2004»
14 years 9 months ago
Three-Dimensional Layers of Maxima
Abstract. We present an O(n log n)-time algorithm to solve the threedimensional layers-of-maxima problem, an improvement over the prior O(n log n log log n)-time solution. A previo...
Adam L. Buchsbaum, Michael T. Goodrich
CVIU
2006
158views more  CVIU 2006»
14 years 9 months ago
Sequential mean field variational analysis of structured deformable shapes
A novel approach is proposed to analyzing and tracking the motion of structured deformable shapes, which consist of multiple correlated deformable subparts. Since this problem is ...
Gang Hua, Ying Wu
SPEECH
1998
118views more  SPEECH 1998»
14 years 9 months ago
Dimensionality reduction of electropalatographic data using latent variable models
We consider the problem of obtaining a reduced dimension representation of electropalatographic (EPG) data. An unsupervised learning approach based on latent variable modelling is...
Miguel Á. Carreira-Perpiñán, ...