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ICML
2008
IEEE
14 years 9 months ago
Discriminative parameter learning for Bayesian networks
Bayesian network classifiers have been widely used for classification problems. Given a fixed Bayesian network structure, parameters learning can take two different approaches: ge...
Jiang Su, Harry Zhang, Charles X. Ling, Stan Matwi...
CVPR
2003
IEEE
14 years 11 months ago
Learning Bayesian Network Classifiers for Facial Expression Recognition using both Labeled and Unlabeled Data
Understanding human emotions is one of the necessary skills for the computer to interact intelligently with human users. The most expressive way humans display emotions is through...
Ira Cohen, Nicu Sebe, Fabio Gagliardi Cozman, Marc...
COLT
2004
Springer
14 years 20 days ago
Regret Bounds for Hierarchical Classification with Linear-Threshold Functions
We study the problem of classifying data in a given taxonomy when classifications associated with multiple and/or partial paths are allowed. We introduce an incremental algorithm u...
Nicolò Cesa-Bianchi, Alex Conconi, Claudio ...
IJON
2006
146views more  IJON 2006»
13 years 9 months ago
Feature selection and classification using flexible neural tree
The purpose of this research is to develop effective machine learning or data mining techniques based on flexible neural tree FNT. Based on the pre-defined instruction/operator se...
Yuehui Chen, Ajith Abraham, Bo Yang
ML
2008
ACM
13 years 8 months ago
Incremental exemplar learning schemes for classification on embedded devices
Although memory-based classifiers offer robust classification performance, their widespread usage on embedded devices is hindered due to the device's limited memory resources...
Ankur Jain, Daniel Nikovski