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KDD
2002
ACM
157views Data Mining» more  KDD 2002»
15 years 11 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
CNSM
2010
14 years 9 months 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
CVPR
2001
IEEE
16 years 1 months ago
Learning Representative Local Features for Face Detection
This paper describes a face detection approach via learning local features. The key idea is that local features, being manifested by a collection of pixels in a local region, are ...
Xiangrong Chen, Lie Gu, Stan Z. Li, HongJiang Zhan...
PAMI
2008
175views more  PAMI 2008»
14 years 11 months ago
Discriminative Feature Co-Occurrence Selection for Object Detection
This paper describes an object detection framework that learns the discriminative co-occurrence of multiple features. Feature co-occurrences are automatically found by Sequential F...
Takeshi Mita, Toshimitsu Kaneko, Björn Stenge...
JIPS
2007
92views more  JIPS 2007»
14 years 11 months ago
Optimization of Domain-Independent Classification Framework for Mood Classification
In this paper, we introduce a domain-independent classification framework based on both k-nearest neighbor and Naïve Bayesian classification algorithms. The architecture of our s...
Sung-Pil Choi, Yuchul Jung, Sung-Hyon Myaeng