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...
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 ...
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...
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...
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...