Séminaires I2M

Functional Data Analysis via Bayesian nonparametrics with application to signal classification\nBy A. Rabaoui\, Institut Fresnel\, Marseille.\n\nIn many signal processing applications\, data collected are drawn from [...]

Toward a general greedy approach for sparse optimization\n\nBy François Xavier Dupé\, LIF.\n\nAbstract : Following recent works on greedy sparse minimization like\nCoSaMP or GRASP\, we propose [...]

Evaluation.\n\nBy Bob Sturm\, Aalborg University Copenhagen.\n\nEvaluation. Evaluating evaluations.* Evaluation of evaluations and their evaluation. Evaluating. Evaluating evaluation and evaluation evaluating. Evaluations of evaluations and evaluating [...]

Inverse Statistical Learning : From minimax to algorithm\n\nBy Sébastien Loustau\, LAREMA\, Univ. Angers.\n\nWe propose to consider the problem of statistical learning when we observe a [...]

De l'imagerie diagnostique à la chirurgie. Ou en sommes nous ? Par Marc-Emmanuel Bellemare (LATP-LSIS) Je présenterai mon activité de recherche en imagerie médicale. J'utiliserai [...]

Curvelets, contourlets, *lets, etc. : a panorama on 2D directional wavelets and multiscale geometric transforms By Laurent Duval, IFP. Abstract: La quête des représentations optimales [...]

Algorithmes d'apprentissage et bornes sur le risque pour l'approche de la régression à la prédiction de structures\nBy Mario Marchand\, Université Laval\, Québec\, Canada.\n\nNous présentons des [...]

Comment interfacer séparation de sources et classification audio?\nBy Emmanuel Vincent\, Inria Nancy - Grand Est.\n\nOn considère le problème de la classification audio au sens large: [...]

Spectral Learning of Hidden Structure or "How NLP (Natural Language Processing) is just a matter of compressive sensing."\nBy Raphaël Bailly\, Universitat Politècnica de Catalunya.\n\nThe spectral [...]

Critical order for moment estimation : insights from statistical physics.\nBy Florian Angeletti ENS Lyon\n\nAbstract:\nMoment estimation is one of the most basic question in statistical signal [...]

Optimal Time-Frequency Bases for EEG Signal Classification in the Context of BCI. by Sebastiano Barbieri\n\nAbstract:\nWe consider the problem of classifying multi-sensor signals\, more\nprecisely EEG signals [...]

Latticial Approach for clustering problems\nBy François Brucker\, Centrale Marseille\, LIF.\n\nWe present a combinatorial model which generalizes phylogenetic trees. This model links together a graph model [...]

Frames adapted to a time-frequency cover\n\nBy Jose Luis Romero \, NuHag\, Vienna\n\nGiven a possibly irregular cover of the time-frequency\nplane\, we construct dictionaries of atoms whose [...]

Large scale network-guided feature selection in genome-wide association mapping. By Chloé-Agathe Azencott, Max Planck Institute. Genome-wide association studies (GWAS)\, in which hundreds of thousands\nor millions [...]

Robust image reconstruction from multi-view measurements.\nBy Pierre Vandergheynst\, EPFL.\n\nWe propose a novel method to accurately reconstruct a set of images representing a single scene from [...]

Solar Rotational Tomography: reconstruction of the electronic density in the Solar Corona.\n\nBy D. Vibert\, LAM\n\nAbstract:\nI will describe the concept of SRT applied to white light [...]

The Posterior Mean of the Total Variation model\nBy Lionel Moisan\, MAP5.\n\nAbstract:\nThe Total Variation image (or signal) denoising model is a variational approach\nthat can be interpreted\, [...]

Title coming soon.\nBy Liva Ralaivola\, LIF.\n\nAbstract coming soon

Sparse dictionary learning in the presence of noise and outliers.\nBy Rémi Gribonval\, INRIA Rennes - Bretagne Atlantique.\n\nA popular approach within the signal processing and machine [...]