• Publications
  • Influence
Y.: SimpleMKL
Multiple kernel learning aims at simultaneously learning a kernel and the associated predictor in supervised learning settings. For the support vector machine, an efficient and general multipleExpand
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BCI Competition III: Dataset II- Ensemble of SVMs for BCI P300 Speller
Brain-computer interface P300 speller aims at helping patients unable to activate muscles to spell words by means of their brain signal activities. Associated to this BCI paradigm, there is theExpand
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Variable Selection Using SVM-based Criteria
We propose new methods to evaluate variable subset relevance with a view to variable selection. Relevance criteria are derived from Support Vector Machines and are based on weight vector ||w||2 orExpand
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A review of classification algorithms for EEG-based brain-computer interfaces: a 10 year update.
OBJECTIVE Most current electroencephalography (EEG)-based brain-computer interfaces (BCIs) are based on machine learning algorithms. There is a large diversity of classifier types that are used inExpand
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Optimal Transport for Domain Adaptation
Domain adaptation is one of the most challenging tasks of modern data analytics. If the adaptation is done correctly, models built on a specific data representation become more robust when confrontedExpand
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More efficiency in multiple kernel learning
An efficient and general multiple kernel learning (MKL) algorithm has been recently proposed by Sonnenburg et al. (2006). This approach has opened new perspectives since it makes the MKL approachExpand
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Recovering Sparse Signals With a Certain Family of Nonconvex Penalties and DC Programming
This paper considers the problem of recovering a sparse signal representation according to a signal dictionary. This problem could be formalized as a penalized least-squares problem in which sparsityExpand
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SVM and Kernel Methods Matlab Toolbox
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Histogram of Gradients of Time–Frequency Representations for Audio Scene Classification
Presents our entry to the Detection and Classification of Acoustic Scenes challenge. The approach we propose for classifying acoustic scenes is based on transforming the audio signal into aExpand
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Pedestrian Detection using Infrared images and Histograms of Oriented Gradients
This paper presents a complete method for pedestrian detection applied to infrared images. First, we study an image descriptor based on histograms of oriented gradients (HOG), associated with aExpand
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