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ICANN
2001
Springer
14 years 2 months ago
Learning and Prediction of the Nonlinear Dynamics of Biological Neurons with Support Vector Machines
Based on biological data we examine the ability of Support Vector Machines (SVMs) with gaussian kernels to learn and predict the nonlinear dynamics of single biological neurons. We...
Thomas Frontzek, Thomas Navin Lal, Rolf Eckmiller
IFIP7
2001
Springer
137views Optimization» more  IFIP7 2001»
14 years 2 months ago
Data Mining via Support Vector Machines
Support vector machines (SVMs) have played a key role in broad classes of problems arising in various fields. Much more recently, SVMs have become the tool of choice for problems...
Olvi L. Mangasarian
NLPRS
2001
Springer
14 years 2 months ago
Unknown Word Guessing and Part-of-Speech Tagging Using Support Vector Machines
The accuracy of part-of-speech (POS) tagging for unknown words is substantially lower than that for known words. Considering the high accuracy rate of up-to-date statistical POS t...
Tetsuji Nakagawa, Taku Kudo, Yuji Matsumoto
CICLING
2006
Springer
14 years 1 months ago
Verb Sense Disambiguation Using Support Vector Machines: Impact of WordNet-Extracted Features
The disambiguation of verbs is usually considered to be more difficult with respect to other part-of-speech categories. This is due both to the high polysemy of verbs compared with...
Davide Buscaldi, Paolo Rosso, Ferran Pla, Encarna ...
EVOW
2006
Springer
14 years 1 months ago
Human Papillomavirus Risk Type Classification from Protein Sequences Using Support Vector Machines
Infection by the human papillomavirus (HPV) is associated with the development of cervical cancer. HPV can be classified to highand low-risk type according to its malignant potenti...
Sun Kim, Byoung-Tak Zhang