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ML
2008
ACM
222views Machine Learning» more  ML 2008»
13 years 8 months ago
Boosted Bayesian network classifiers
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
Yushi Jing, Vladimir Pavlovic, James M. Rehg
IJCAI
2007
13 years 10 months ago
Learning to Identify Unexpected Instances in the Test Set
Traditional classification involves building a classifier using labeled training examples from a set of predefined classes and then applying the classifier to classify test instan...
Xiaoli Li, Bing Liu, See-Kiong Ng
MCS
2004
Springer
14 years 2 months ago
Learn++.MT: A New Approach to Incremental Learning
An ensemble of classifiers based algorithm, Learn++, was recently introduced that is capable of incrementally learning new information from datasets that consecutively become avail...
Michael Muhlbaier, Apostolos Topalis, Robi Polikar
ICASSP
2010
IEEE
13 years 8 months ago
Classifying laughter and speech using audio-visual feature prediction
In this study, a system that discriminates laughter from speech by modelling the relationship between audio and visual features is presented. The underlying assumption is that thi...
Stavros Petridis, Ali Asghar, Maja Pantic
BMCBI
2006
150views more  BMCBI 2006»
13 years 8 months ago
Predicting protein subcellular locations using hierarchical ensemble of Bayesian classifiers based on Markov chains
Background: The subcellular location of a protein is closely related to its function. It would be worthwhile to develop a method to predict the subcellular location for a given pr...
Alla Bulashevska, Roland Eils