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» Feature selection for linear support vector machines
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BMCBI
2007
178views more  BMCBI 2007»
13 years 8 months ago
SVM clustering
Background: Support Vector Machines (SVMs) provide a powerful method for classification (supervised learning). Use of SVMs for clustering (unsupervised learning) is now being cons...
Stephen Winters-Hilt, Sam Merat
CLEF
2008
Springer
13 years 10 months ago
RAVE: A Fast Logic-Based Answer Validator
RAVE (Real-time Answer Validation Engine) is a logic-based answer validator/selector designed for real-time question answering. Instead of proving a hypothesis for each answer, RAV...
Ingo Glöckner
ICIP
2005
IEEE
14 years 10 months ago
Eigenwalks: walk detection and biometrics from symmetry patterns
In this paper we present a symmetry-based approach which can be used to detect humans and to extract biometric characteristics from video image-sequences. The method employs a simp...
Laszlo Havasi, Tamás Szirányi, Zolt&...
ISBI
2006
IEEE
14 years 9 months ago
Automated segmentation of white matter lesions in 3D brain MR images, using multivariate pattern classification
This paper presents a fully automatic white matter lesion (WML) segmentation method, based on local features determined by combining multiple MR acquisition protocols, including T...
Abbas Jawad, Bilge Karaçali, Christos Davat...
KDD
2002
ACM
179views Data Mining» more  KDD 2002»
14 years 8 months ago
Combining clustering and co-training to enhance text classification using unlabelled data
In this paper, we present a new co-training strategy that makes use of unlabelled data. It trains two predictors in parallel, with each predictor labelling the unlabelled data for...
Bhavani Raskutti, Herman L. Ferrá, Adam Kow...