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» Learning the Dimensionality of Hidden Variables
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ICML
2007
IEEE
16 years 16 days ago
Multifactor Gaussian process models for style-content separation
We introduce models for density estimation with multiple, hidden, continuous factors. In particular, we propose a generalization of multilinear models using nonlinear basis functi...
Jack M. Wang, David J. Fleet, Aaron Hertzmann
IJCNN
2007
IEEE
15 years 6 months ago
A Wrapper for Projection Pursuit Learning
– Constructive algorithms are effective methods for designing Artificial Neural Networks (ANN) with good accuracy and generalization capability, yet with parsimonious network str...
Leonardo M. Holschuh, Clodoaldo Ap. M. Lima, Ferna...
CAIP
2003
Springer
222views Image Analysis» more  CAIP 2003»
15 years 5 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
EMNLP
2007
15 years 1 months ago
A Topic Model for Word Sense Disambiguation
We develop latent Dirichlet allocation with WORDNET (LDAWN), an unsupervised probabilistic topic model that includes word sense as a hidden variable. We develop a probabilistic po...
Jordan L. Boyd-Graber, David M. Blei, Xiaojin Zhu
ISDA
2010
IEEE
14 years 9 months ago
Feature selection is the ReliefF for multiple instance learning
Dimensionality reduction and feature selection in particular are known to be of a great help for making supervised learning more effective and efficient. Many different feature sel...
Amelia Zafra, Mykola Pechenizkiy, Sebastián...