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» Learning with Rigorous Support Vector Machines
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ICML
2004
IEEE
16 years 7 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
16 years 9 days 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 9 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 10 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 11 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