80 search results - page 7 / 16 » Racing for Conditional Independence Inference |
ICML
2005
IEEE
15 years 10 months ago
2005
IEEE
Naive Bayes models have been widely used for clustering and classification. However, they are seldom used for general probabilistic learning and inference (i.e., for estimating an...
MICAI
2007
Springer
15 years 3 months ago
2007
Springer
Previous work on context-specific independence in Bayesian networks is driven by a common goal, namely to represent the conditional probability tables in a most compact way. In th...
CORR
2004
Springer
14 years 9 months ago
2004
Springer
We define the concept of dependence among multiple variables using maximum entropy techniques and introduce a graphical notation to denote the dependencies. Direct inference of in...
NIPS
1997
14 years 11 months ago
1997
We address the problem of learning structure in nonlinear Markov networks with continuous variables. This can be viewed as non-Gaussian multidimensional density estimation exploit...
BMCBI
2011
14 years 4 months ago
2011
Background: With the growing availability of entire genome sequences, an increasing number of scientists can exploit oligonucleotide microarrays for genome-scale expression studie...