1864 search results - page 19 / 373 » Modeling Classification and Inference Learning |
FLAIRS
2006
13 years 10 months ago
2006
A major difficulty in building Bayesian network models is the size of conditional probability tables, which grow exponentially in the number of parents. One way of dealing with th...
ICML
2004
IEEE
14 years 10 months ago
2004
IEEE
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
JMLR
2010
13 years 3 months ago
2010
Probabilistic models of the performance of computer systems are useful both for predicting system performance in new conditions, and for diagnosing past performance problems. The ...
COLING
2002
13 years 9 months ago
2002
This paper proposes an unsupervised learning model for classifying named entities. This model uses a training set, built automatically by means of a small-scale named entity dicti...
JMLR
2010
13 years 3 months ago
2010
The FastInf C++ library is designed to perform memory and time efficient approximate inference in large-scale discrete undirected graphical models. The focus of the library is pro...