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» Learning of Boolean Functions Using Support Vector Machines
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ICML
2003
IEEE
14 years 8 months ago
Using Linear-threshold Algorithms to Combine Multi-class Sub-experts
We present a new type of multi-class learning algorithm called a linear-max algorithm. Linearmax algorithms learn with a special type of attribute called a sub-expert. A sub-exper...
Chris Mesterharm
ISBI
2004
IEEE
14 years 8 months ago
Qualitative Asymmetry Measure for Melanoma Detection
Size Functions and Support Vector Machines are used to implement a new automatic classifier of melanocytic lesions. This is mainly based on a qualitative assessment of asymmetry. ...
Michele d'Amico, Massimo Ferri, Ignazio Stanganell...
BMCBI
2007
153views more  BMCBI 2007»
13 years 7 months ago
Analysis of nanopore detector measurements using Machine-Learning methods, with application to single-molecule kinetic analysis
Background: A nanopore detector has a nanometer-scale trans-membrane channel across which a potential difference is established, resulting in an ionic current through the channel ...
Matthew Landry, Stephen Winters-Hilt
ICRA
2006
IEEE
100views Robotics» more  ICRA 2006»
14 years 1 months ago
Learning EMG Control of a Robotic Hand: Towards Active Prostheses
— We introduce a method based on support vector machines which can detect opening and closing actions of the human thumb, index finger, and other fingers recorded via surface E...
Sebastian Bitzer, P. Patrick van der Smagt
ICML
2003
IEEE
14 years 8 months ago
Discriminative Gaussian Mixture Models: A Comparison with Kernel Classifiers
We show that a classifier based on Gaussian mixture models (GMM) can be trained discriminatively to improve accuracy. We describe a training procedure based on the extended Baum-W...
Aldebaro Klautau, Nikola Jevtic, Alon Orlitsky