JMLR
2010
12 years 11 months ago
2010
Bayesian principal component analysis (BPCA), a probabilistic reformulation of PCA with Bayesian model selection, is a systematic approach to determining the number of essential p...
Presentation
Presentation of the exponential families, of the mixtures of such distributions and how to learn it. We then present algorithms to simplify mixture model, using Kullback-Leibler di...
ICASSP
2010
IEEE
13 years 4 months ago
2010
IEEE
The exponential embedding of two or more probability density functions (PDFs) is proposed for multimodal sensor processing. It approximates the unknown PDF by exponentially embedd...
NIPS
2004
13 years 5 months ago
2004
Directed graphical models with one layer of observed random variables and one or more layers of hidden random variables have been the dominant modelling paradigm in many research ...
NIPS
2008
13 years 6 months ago
2008
Recently, supervised dimensionality reduction has been gaining attention, owing to the realization that data labels are often available and indicate important underlying structure...
ISIPTA
2005
IEEE
13 years 10 months ago
2005
IEEE
When considering sampling models described by a distribution from an exponential family, it is possible to create two types of imprecise probability models. One is based on the co...
SCALESPACE
2009
Springer
13 years 11 months ago
2009
Springer
In this work, we propose novel results for the optimization of divergences within the framework of region-based active contours. We focus on parametric statistical models where th...