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» On Learning Decision Trees with Large Output Domains
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ICASSP
2010
IEEE
13 years 8 months ago
Language model adaptation using Random Forests
In this paper we investigate random forest based language model adaptation. Large amounts of out-of-domain data are used to grow the decision trees while very small amounts of in-...
Anoop Deoras, Frederick Jelinek, Yi Su
IJSI
2008
156views more  IJSI 2008»
13 years 7 months ago
Co-Training by Committee: A Generalized Framework for Semi-Supervised Learning with Committees
Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
Mohamed Farouk Abdel Hady, Friedhelm Schwenker
ISVC
2010
Springer
13 years 6 months ago
On Supervised Human Activity Analysis for Structured Environments
We consider the problem of developing an automated visual solution for detecting human activities within industrial environments. This has been performed using an overhead view. Th...
Banafshe Arbab-Zavar, Imed Bouchrika, John N. Cart...
BMCBI
2006
137views more  BMCBI 2006»
13 years 7 months ago
A classification-based framework for predicting and analyzing gene regulatory response
Background: We have recently introduced a predictive framework for studying gene transcriptional regulation in simpler organisms using a novel supervised learning algorithm called...
Anshul Kundaje, Manuel Middendorf, Mihir Shah, Chr...
PAA
2002
13 years 7 months ago
Hierarchical Fusion of Multiple Classifiers for Hyperspectral Data Analysis
: Many classification problems involve high dimensional inputs and a large number of classes. Multiclassifier fusion approaches to such difficult problems typically centre around s...
Shailesh Kumar, Joydeep Ghosh, Melba M. Crawford