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» State-Space Inference and Learning with Gaussian Processes
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ICML
2006
IEEE
16 years 2 months ago
Probabilistic inference for solving discrete and continuous state Markov Decision Processes
Inference in Markov Decision Processes has recently received interest as a means to infer goals of an observed action, policy recognition, and also as a tool to compute policies. ...
Marc Toussaint, Amos J. Storkey
ICCV
2011
IEEE
14 years 1 months ago
Shape-constrained Gaussian Process Regression for Facial-point-based Head-pose Normalization
Given the facial points extracted from an image of a face in an arbitrary pose, the goal of facial-point-based headpose normalization is to obtain the corresponding facial points ...
Ognjen Rudovic, Maja Pantic
ICIP
2005
IEEE
16 years 3 months ago
SAR images as mixtures of Gaussian mixtures
We consider the problem of image segmentation by clustering local histograms with parametric mixture-of-mixture models. These models represent each cluster by a single mixture mod...
Peter Orbanz, Joachim M. Buhmann
JMLR
2012
13 years 3 months ago
A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models
The development of accurate models and efficient algorithms for the analysis of multivariate categorical data are important and longstanding problems in machine learning and compu...
Mohammad Emtiyaz Khan, Shakir Mohamed, Benjamin M....
ICML
2004
IEEE
16 years 2 months ago
Variational methods for the Dirichlet process
Variational inference methods, including mean field methods and loopy belief propagation, have been widely used for approximate probabilistic inference in graphical models. While ...
David M. Blei, Michael I. Jordan