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IJSI
2008
156views more  IJSI 2008»
13 years 9 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
KAIS
2006
110views more  KAIS 2006»
13 years 9 months ago
Multi-step density-based clustering
Abstract. Data mining in large databases of complex objects from scientific, engineering or multimedia applications is getting more and more important. In many areas, complex dista...
Stefan Brecheisen, Hans-Peter Kriegel, Martin Pfei...
TCSV
2008
195views more  TCSV 2008»
13 years 9 months ago
Locality Versus Globality: Query-Driven Localized Linear Models for Facial Image Computing
Conventional subspace learning or recent feature extraction methods consider globality as the key criterion to design discriminative algorithms for image classification. We demonst...
Yun Fu, Zhu Li, Junsong Yuan, Ying Wu, Thomas S. H...
AI
2002
Springer
13 years 9 months ago
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
Zhi-Hua Zhou, Jianxin Wu, Wei Tang
ECCC
2000
140views more  ECCC 2000»
13 years 9 months ago
Randomized Approximation Schemes for Scheduling Unrelated Parallel Machines
We consider the problem of Scheduling n Independent Jobs on m Unrelated Parallel Machines, when the number of machines m is xed. We address the standard problem of minimizing the ...
Pavlos Efraimidis, Paul G. Spirakis