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» Substring Selectivity Estimation
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CORR
2007
Springer
128views Education» more  CORR 2007»
13 years 8 months ago
Model Selection Through Sparse Maximum Likelihood Estimation
We consider the problem of estimating the parameters of a Gaussian or binary distribution in such a way that the resulting undirected graphical model is sparse. Our approach is to...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
ICASSP
2011
IEEE
13 years 4 days ago
On selecting the hyperparameters of the DPM models for the density estimation of observation errors
The Dirichlet Process Mixture (DPM) models represent an attractive approach to modeling latent distributions parametrically. In DPM models the Dirichlet process (DP) is applied es...
Asma Rabaoui, Nicolas Viandier, Juliette Marais, E...
ICML
2007
IEEE
14 years 9 months ago
Supervised feature selection via dependence estimation
We introduce a framework for filtering features that employs the Hilbert-Schmidt Independence Criterion (HSIC) as a measure of dependence between the features and the labels. The ...
Le Song, Alex J. Smola, Arthur Gretton, Karsten M....
CIVR
2004
Springer
128views Image Analysis» more  CIVR 2004»
14 years 1 months ago
A Geometrical Key-Frame Selection Method Exploiting Dominant Motion Estimation in Video
We describe an original method for selecting key frames to represent the content of every shot in a video. We aim at spatially sampling in an uniform way the coverage of the scene ...
Brigitte Fauvet, Patrick Bouthemy, Patrick Gros, F...
CSDA
2010
208views more  CSDA 2010»
13 years 8 months ago
Bayesian density estimation and model selection using nonparametric hierarchical mixtures
We consider mixtures of parametric densities on the positive reals with a normalized generalized gamma process (Brix, 1999) as mixing measure. This class of mixtures encompasses t...
Raffaele Argiento, Alessandra Guglielmi, Antonio P...