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» Learning with Rigorous Support Vector Machines
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ICML
2004
IEEE
16 years 4 months ago
Links between perceptrons, MLPs and SVMs
We propose to study links between three important classification algorithms: Perceptrons, Multi-Layer Perceptrons (MLPs) and Support Vector Machines (SVMs). We first study ways to...
Ronan Collobert, Samy Bengio
MLMI
2007
Springer
15 years 10 months ago
Conditional Sequence Model for Context-Based Recognition of Gaze Aversion
Eye gaze and gesture form key conversational grounding cues that are used extensively in face-to-face interaction among people. To accurately recognize visual feedback during inter...
Louis-Philippe Morency, Trevor Darrell
ECML
2006
Springer
15 years 7 months ago
Sequence Discrimination Using Phase-Type Distributions
Abstract We propose in this paper a novel approach to the classification of discrete sequences. This approach builds a model fitting some dynamical features deduced from the learni...
Jérôme Callut, Pierre Dupont
ICASSP
2011
IEEE
14 years 7 months ago
SVM feature selection for multidimensional EEG data
In many machine learning applications, like Brain - Computer Interfaces (BCI), only high-dimensional noisy data are available rendering the discrimination task non-trivial. In thi...
Nisrine Jrad, Ronald Phlypo, Marco Congedo
ICAISC
2004
Springer
15 years 9 months ago
Relevance LVQ versus SVM
Abstract. The support vector machine (SVM) constitutes one of the most successful current learning algorithms with excellent classification accuracy in large real-life problems an...
Barbara Hammer, Marc Strickert, Thomas Villmann