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KDD
2002
ACM
157views Data Mining» more  KDD 2002»
16 years 2 months ago
Exploiting unlabeled data in ensemble methods
An adaptive semi-supervised ensemble method, ASSEMBLE, is proposed that constructs classification ensembles based on both labeled and unlabeled data. ASSEMBLE alternates between a...
Kristin P. Bennett, Ayhan Demiriz, Richard Maclin
115
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CNSM
2010
15 years 16 days ago
An investigation on the identification of VoIP traffic: Case study on Gtalk and Skype
The classification of encrypted traffic on the fly from network traces represents a particularly challenging application domain. Recent advances in machine learning provide the opp...
Riyad Alshammari, A. Nur Zincir-Heywood
121
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ECCV
2008
Springer
16 years 4 months ago
3D Face Recognition by Local Shape Difference Boosting
Abstract. A new approach, called Collective Shape Difference Classifier (CSDC), is proposed to improve the accuracy and computational efficiency of 3D face recognition. The CSDC le...
Yueming Wang, Xiaoou Tang, Jianzhuang Liu, Gang Pa...
ICPR
2008
IEEE
16 years 3 months ago
Pattern rejection strategies for the design of self-paced EEG-based Brain-Computer Interfaces
This paper deals with pattern rejection strategies for self-paced Brain-Computer Interfaces (BCI). First, it introduces two pattern rejection strategies not used yet for self-pace...
Fabien Lotte, Harold Mouchère, Anatole L&ea...
121
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DATAMINE
2006
157views more  DATAMINE 2006»
15 years 2 months ago
Data Clustering with Partial Supervision
Clustering with partial supervision finds its application in situations where data is neither entirely nor accurately labeled. This paper discusses a semisupervised clustering algo...
Abdelhamid Bouchachia, Witold Pedrycz