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IJCNN
2008
IEEE
14 years 3 months ago
Ranking and selecting clustering algorithms using a meta-learning approach
Abstract— We present a novel framework that applies a metalearning approach to clustering algorithms. Given a dataset, our meta-learning approach provides a ranking for the candi...
Marcílio Carlos Pereira de Souto, Ricardo B...
BMCBI
2010
182views more  BMCBI 2010»
13 years 9 months ago
L2-norm multiple kernel learning and its application to biomedical data fusion
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
Shi Yu, Tillmann Falck, Anneleen Daemen, Lé...
KDD
2006
ACM
170views Data Mining» more  KDD 2006»
14 years 9 months ago
Computer aided detection via asymmetric cascade of sparse hyperplane classifiers
This paper describes a novel classification method for computer aided detection (CAD) that identifies structures of interest from medical images. CAD problems are challenging larg...
Jinbo Bi, Senthil Periaswamy, Kazunori Okada, Tosh...
ICASSP
2009
IEEE
13 years 7 months ago
Phonological features in discriminative classification of dysarthric speech
In an attempt to overcome problems associated with articulatory limitations and generative models, this work considers the use of phonological features in discriminative models fo...
Frank Rudzicz
EMNLP
2010
13 years 7 months ago
A Semi-Supervised Approach to Improve Classification of Infrequent Discourse Relations Using Feature Vector Extension
Several recent discourse parsers have employed fully-supervised machine learning approaches. These methods require human annotators to beforehand create an extensive training corp...
Hugo Hernault, Danushka Bollegala, Mitsuru Ishizuk...