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» Universality Results for Models in Locally Boolean Domains
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NN
2006
Springer
114views Neural Networks» more  NN 2006»
13 years 8 months ago
Modular learning models in forecasting natural phenomena
Modular model is a particular type of committee machine and is comprised of a set of specialized (local) models each of which is responsible for a particular region of the input s...
Dimitri P. Solomatine, Michael Baskara L. A. Siek
CVPR
2009
IEEE
15 years 3 months ago
A Revisit of Generative Model for Automatic Image Annotation using Markov Random Fields
Much research effort on Automatic Image Annotation (AIA) has been focused on Generative Model, due to its well formed theory and competitive performance as compared with many we...
Yu Xiang (Fudan University), Xiangdong Zhou (Fudan...
UAI
1993
13 years 10 months ago
Using Causal Information and Local Measures to Learn Bayesian Networks
In previous work we developed a method of learning Bayesian Network models from raw data. This method relies on the well known minimal description length (MDL) principle. The MDL ...
Wai Lam, Fahiem Bacchus
KES
2004
Springer
14 years 2 months ago
Extracting Stellar Population Parameters of Galaxies from Photometric Data Using Evolution Strategies and Locally Weighted Linea
There is now a huge amount of high quality photometric data available in the literature whose analysis is bound to play a fundamental role in studies of the formation and evolution...
Luis Alvarez, Olac Fuentes, Roberto Terlevich
BMCBI
2008
116views more  BMCBI 2008»
13 years 8 months ago
IgTM: An algorithm to predict transmembrane domains and topology in proteins
Background: Due to their role of receptors or transporters, membrane proteins play a key role in many important biological functions. In our work we used Grammatical Inference (GI...
Piedachu Peris, Damián López, Marcel...