Augmented-SVM
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Women in Science and Engineering. EPFL, Ecole Polytechnique Federale de Lausanne. CH 1015, Lausanne, Switzerland. Machine Learning with Application to Robotics. Computational Neuroscience and Cognitive Modeling.
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Is a novel support vector formulation that generalizes the classical Support Vector Machine. This framework can be used to learn a non-linear classifierregression function by simultaneously taking into account constraints equality or inequality on the function value and the gradient. This work was first presented in the following paper . Volume 25, Pages 1025-1033. pdf. From SVM to A-SVM. And regression problems are composed of equality constraints. Is the required function,. For control applicatio.PARSED CONTENT
The site asvm.epfl.ch states the following, "Is a novel support vector formulation that generalizes the classical Support Vector Machine." I noticed that the webpage said " This framework can be used to learn a non-linear classifierregression function by simultaneously taking into account constraints equality or inequality on the function value and the gradient." They also stated " This work was first presented in the following paper . Volume 25, Pages 1025-1033. And regression problems are composed of equality constraints. Is the required function,."ANALYZE MORE WEB SITES
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