Localisation

Adresses

Aix-Marseille Université
Institut de Mathématiques de Marseille (I2M) - UMR 7373
Site Saint-Charles : 3 place Victor Hugo, Case 19, 13331 Marseille Cedex 3
Site Luminy : Campus de Luminy - Case 907 - 13288 Marseille Cedex 9

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Séminaire

J. Lefèvre (LSIS): Harmonic analysis on manifolds: recent applications in neuroimaging data

07/03/2013 @ 14h00 – 15h00 – Harmonic analysis on manifolds: recent applications in neuroimaging data By Julien Lefèvre, LSIS. This talk aims at introducing some mathematical tools of harmonic analysis on non-euclidian domains, typically Riemannian manifolds, and to show illustrative applications for surfaces in R^3. In parallel I will refer to a discrete version of this framework by considering graph laplacian. […]

Séminaire

M. Unser (EPFL) Tutorial: Sparse stochastic processes and biomedical image reconstruction

04/02/2013 @ 14h00 – 16h00 – By Michael Unser\, EPFL.\n\nTutorial: Sparse stochastic processes and biomedical image reconstruction\n\nSparse stochastic processes are continuous-domain processes that admit a parsimonious representation in some matched wavelet-like basis. Such models are relevant for image compression\, compressed sensing\, and\, more generally\, for the derivation of statistical algorithms for solving ill-posed inverse problems.\n\nThis tutorial focuses on an extended family […]

Séminaire

E. Vural (EPFL): Transformation-invariant analysis of visual signals with manifold models

31/01/2013 @ 14h00 – 15h00 – Transformation-invariant analysis of visual signals with manifold models By Elif Vural, EPFL. Manifold models provide low-dimensional representations that are useful for processing and analyzing visual signals in a transformation-invariant way. The set of images generated by the geometric transformations of a reference visual pattern is called the transformation manifold of that pattern. In an image […]

Séminaire

G. Gassier (IM2NP): Subspaces methods in passive radar

24/01/2013 @ 14h00 – 15h00 – Subspaces methods in passive radar.\nBy Ghislain Gassier\, IM2NP.\nA bistatic passive Doppler radar system exploits already existing RF transmitters (illuminators of opportunity) to detect and localize moving targets. Our interest is focused on Digital Video Broadcasting-Terrestrial (DVB-T) signals which exhibit a wide bandwidth\, providing an interest- ing resolution in terms of bistatic range.\nIn passive radar\, the […]

Séminaire

P. Réfregier (Institut Fresnel): Cramer-Rao Bound and application to radar and optical polarimetry

10/01/2013 @ 14h00 – 15h00 – Title: Cramer-Rao Bound and application to radar and optical polarimetry. By Philippe Réfregier, Institut Fresnel. During this talk, we will try to illustrate estimation precision characterization techniques for two applications of polarimetric measuments. The first one concerns optical microscopy polarimetry with second order nonlinearities. The goal consists in estimating structural parameters of the distribution of […]

Séminaire

J. Marchi (INS) : Fully unsupervised detection and clustering of EEG epileptic spikes

13/12/2012 @ 14h00 – 15h00 – Fully unsupervised detection and clustering of EEG epileptic spikes. By Johann Marchi, INS. Nowadays, large amounts of electroencephalogram (EEG) data remain unexploited because of a lack of unsupervised data mining programs. Indeed, the visual analysis of EEG signals is a time-consuming task for the physician, and some variability may appear across expert advice, hence the […]

Séminaire

Online confusion learning and passive-aggressive scheme.

22/11/2012 @ 14h00 – 15h00 – Online confusion learning and passive-aggressive scheme By Liva Ralaivola, LIF. This work provides the first — to the best of our knowledge — analysis of online learning algorithms for multiclass problems when the confusion matrix is taken as a performance measure. The work builds upon recent and elegant results on non- commutative concentration inequalities, i.e. […]

Séminaire

E. Morvant (LIF): A Well-founded PAC-Bayesian Majority Vote applied to the Nearest Neighbor Rule

15/11/2012 @ 14h00 – 15h00 – A Well-founded PAC-Bayesian Majority Vote applied to the Nearest Neighbor Rule\n\nBy Emilie Morvant\, LIF.\n\nThe Nearest Neighbor (NN) [1] rule is probably the best-known classification method. Its widespread use in machine learning and pattern recognition is due to its simplicity\, its theoretical properties and its good practical performance. In this work\, we focus on the k-NN […]

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