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» Learning Classifiers from Semantically Heterogeneous Data
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SDM
2010
SIAM
144views Data Mining» more  SDM 2010»
13 years 10 months ago
Predictive Modeling with Heterogeneous Sources
Lack of labeled training examples is a common problem for many applications. In the same time, there is usually an abundance of labeled data from related tasks. But they have diff...
Xiaoxiao Shi, Qi Liu, Wei Fan, Qiang Yang, Philip ...
MCS
2007
Springer
14 years 3 months ago
An Ensemble Approach for Incremental Learning in Nonstationary Environments
Abstract. We describe an ensemble of classifiers based algorithm for incremental learning in nonstationary environments. In this formulation, we assume that the learner is presente...
Michael Muhlbaier, Robi Polikar
CORR
2008
Springer
94views Education» more  CORR 2008»
13 years 9 months ago
Decision Support with Belief Functions Theory for Seabed Characterization
The seabed characterization from sonar images is a very hard task because of the produced data and the unknown environment, even for an human expert. In this work we propose an ori...
Arnaud Martin, Isabelle Quidu
SCCC
2000
IEEE
14 years 1 months ago
A Genetic Classifier Tool
Knowledge discovery is the most desirable end product of an enterprise information system. Researches from different areas recognize that a new generation of intelligent tools for...
Aurora T. R. Pozo, Mozart Hasse
ICASSP
2007
IEEE
14 years 3 months ago
Integrating Relevance Feedback in Boosting for Content-Based Image Retrieval
Many content-based image retrieval applications suffer from small sample set and high dimensionality problems. Relevance feedback is often used to alleviate those problems. In thi...
Jie Yu, Yijuan Lu, Yuning Xu, Nicu Sebe, Qi Tian