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» Continuous Gaussian Mixture Modeling
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NIPS
1996
14 years 11 months ago
Continuous Sigmoidal Belief Networks Trained using Slice Sampling
Real-valued random hidden variables can be useful for modelling latent structure that explains correlations among observed variables. I propose a simple unit that adds zero-mean G...
Brendan J. Frey
ICPR
2010
IEEE
15 years 4 months ago
Gait Learning-Based Regenerative Model: A Level Set Approach
We propose a learning method for gait synthesis from a sequence of shapes(frames) with the ability to extrapolate to novel data. It involves the application of PCA, first to redu...
Muayed Sattar Al-Huseiny, Sasan Mahmoodi, Mark Nix...
NIPS
2001
14 years 11 months ago
Covariance Kernels from Bayesian Generative Models
We propose the framework of mutual information kernels for learning covariance kernels, as used in Support Vector machines and Gaussian process classifiers, from unlabeled task da...
Matthias Seeger
SAC
2011
ACM
14 years 4 months ago
Slice sampling mixture models
We propose a more efficient version of the slice sampler for Dirichlet process mixture models described by Walker (2007). This sampler allows the fitting of infinite mixture mod...
Maria Kalli, Jim E. Griffin, Stephen G. Walker
TCSV
2010
14 years 4 months ago
Video Foreground Detection Based on Symmetric Alpha-Stable Mixture Models
Background subtraction (BS) is an efficient technique for detecting moving objects in video sequences. A simple BS process involves building a model of the background and extractin...
Harish Bhaskar, Lyudmila Mihaylova, Alin Achim