79 search results - page 10 / 16 » Imprecise probability models for inference in exponential fa... |
ICASSP
2010
IEEE
13 years 7 months ago
2010
IEEE
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
ICDM
2007
IEEE
14 years 2 months ago
2007
IEEE
In spite of the popularity of probabilistic mixture models for latent structure discovery from data, mixture models do not have a natural mechanism for handling sparsity, where ea...
AAAI
2006
13 years 9 months ago
2006
This paper presents multi-conditional learning (MCL), a training criterion based on a product of multiple conditional likelihoods. When combining the traditional conditional proba...
JAIR
1998
13 years 7 months ago
1998
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
CSB
2002
IEEE
14 years 19 days ago
2002
IEEE
Analyzing protein sequence data becomes increasingly important recently. Most previous work on this area has mainly focused on building classification models. In this paper, we i...