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» Gaussian processes and limiting linear models
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CVPR
2008
IEEE
14 years 5 months ago
A theoretical analysis of linear and multi-linear models of image appearance
Linear and multi-linear models of object shape/appearance (PCA, 3DMM, AAM/ASM, multilinear tensors) have been very popular in computer vision. In this paper, we analyze the validi...
Yilei Xu, Amit K. Roy Chowdhury
ICASSP
2009
IEEE
14 years 5 months ago
Time-space-sequential algorithms for distributed Bayesian state estimation in serial sensor networks
We consider distributed estimation of a time-dependent, random state vector based on a generally nonlinear/non-Gaussian state-space model. The current state is sensed by a serial ...
Ondrej Hlinka, Franz Hlawatsch
NIPS
2000
14 years 7 days ago
Occam's Razor
The Bayesian paradigm apparently only sometimes gives rise to Occam's Razor; at other times very large models perform well. We give simple examples of both kinds of behaviour...
Carl Edward Rasmussen, Zoubin Ghahramani
ICCV
2009
IEEE
13 years 8 months ago
Bayesian Poisson regression for crowd counting
Poisson regression models the noisy output of a counting function as a Poisson random variable, with a log-mean parameter that is a linear function of the input vector. In this wo...
Antoni B. Chan, Nuno Vasconcelos
ICASSP
2011
IEEE
13 years 2 months ago
Factored covariance modeling for text-independent speaker verification
Gaussian mixture models (GMMs) are commonly used to model the spectral distribution of speech signals for text-independent speaker verification. Mean vectors of the GMM, used in c...
Eryu Wang, Kong-Aik Lee, Bin Ma, Haizhou Li, Wu Gu...