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» Density Estimation Using Mixtures of Mixtures of Gaussians
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ICASSP
2011
IEEE
14 years 5 months ago
Bayesian sensing hidden Markov models for speech recognition
We introduce Bayesian sensing hidden Markov models (BS-HMMs) to represent speech data based on a set of state-dependent basis vectors. By incorporating the prior density of sensin...
George Saon, Jen-Tzung Chien
ICA
2004
Springer
15 years 7 months ago
Wavelet De-noising for Blind Source Separation in Noisy Mixtures
Blind source separation, which supposes that the sources are independent, is a well known domain in signal processing. However, in a noisy environment the estimation of the criteri...
Bertrand Rivet, Vincent Vigneron, Anisoara Parasch...
ICPR
2004
IEEE
16 years 3 months ago
Visual Learning and Recognition of a Probabilistic Spatio-Temporal Model of Cyclic Human Locomotion
We present a novel representation of cyclic human locomotion based on a set of spatio-temporal curves of tracked points on the surface of a person. We start by extracting a set of...
Miha Peternel, Ales Leonardis
ICIP
2009
IEEE
16 years 3 months ago
Image Restoration By Mixture Modelling Of An Overcomplete Linear Representation
We present a new image restoration method based on modelling the coefficients of an overcomplete wavelet response to natural images with a mixture of two Gaussian distributions, h...
JMLR
2010
118views more  JMLR 2010»
14 years 8 months ago
Dirichlet Process Mixtures of Generalized Linear Models
We propose Dirichlet Process mixtures of Generalized Linear Models (DP-GLMs), a new method of nonparametric regression that accommodates continuous and categorical inputs, models ...
Lauren Hannah, David M. Blei, Warren B. Powell