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121
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ICML
2006
IEEE
16 years 3 months ago
Simpler knowledge-based support vector machines
If appropriately used, prior knowledge can significantly improve the predictive accuracy of learning algorithms or reduce the amount of training data needed. In this paper we intr...
Quoc V. Le, Alex J. Smola, Thomas Gärtner
CGF
2005
252views more  CGF 2005»
15 years 2 months ago
Support Vector Machines for 3D Shape Processing
We propose statistical learning methods for approximating implicit surfaces and computing dense 3D deformation fields. Our approach is based on Support Vector (SV) Machines, which...
Florian Steinke, Bernhard Schölkopf, Volker B...
ICDAR
2005
IEEE
15 years 8 months ago
Language Identification of Character Images Using Machine Learning Techniques
In this paper, we propose a new approach for identifying the language type of character images. We do this by classifying individual character images to determine the language bou...
Ying-Ho Liu, Fu Chang, Chin-Chin Lin
IJCNLP
2005
Springer
15 years 7 months ago
Assigning Polarity Scores to Reviews Using Machine Learning Techniques
We propose a novel type of document classification task that quantifies how much a given document (review) appreciates the target object using not binary polarity (good or bad) b...
Daisuke Okanohara, Jun-ichi Tsujii
84
Voted
BMCBI
2008
88views more  BMCBI 2008»
15 years 2 months ago
Use of machine learning algorithms to classify binary protein sequences as highly-designable or poorly-designable
Background: By using a standard Support Vector Machine (SVM) with a Sequential Minimal Optimization (SMO) method of training, Na
Myron Peto, Andrzej Kloczkowski, Vasant Honavar, R...