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CORR
2006
Springer
99views Education» more  CORR 2006»
14 years 12 months ago
PAC Learning Mixtures of Axis-Aligned Gaussians with No Separation Assumption
Abstract. We propose and analyze a new vantage point for the learning of mixtures of Gaussians: namely, the PAC-style model of learning probability distributions introduced by Kear...
Jon Feldman, Ryan O'Donnell, Rocco A. Servedio
TIP
2008
163views more  TIP 2008»
14 years 11 months ago
Image Modeling and Denoising With Orientation-Adapted Gaussian Scale Mixtures
We develop a statistical model to describe the spatially varying behavior of local neighborhoods of coefficients in a multiscale image representation. Neighborhoods are modeled as ...
David K. Hammond, Eero P. Simoncelli
ISVC
2010
Springer
14 years 10 months ago
Bivariate Feature Localization for SIFT Assuming a Gaussian Feature Shape
In this paper, the well-known SIFT detector is extended with a bivariate feature localization. This is done by using function models that assume a Gaussian feature shape for the de...
Kai Cordes, Oliver Müller, Bodo Rosenhahn, J&...
JMLR
2010
155views more  JMLR 2010»
14 years 6 months ago
Bayesian Gaussian Process Latent Variable Model
We introduce a variational inference framework for training the Gaussian process latent variable model and thus performing Bayesian nonlinear dimensionality reduction. This method...
Michalis Titsias, Neil D. Lawrence