Séminaires I2M

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 [...]

Estimation of frequency modulations on wideband signals\, applications to audio signal analysis\n\nBy Harold Omer\, LATP.\n\nAbstract:\nThe problem of joint estimation of power spectrum and modulation from [...]

Pédagogies innovantes actives - retour d'expérience et discussion\nPar Bertrand David\, Télécom ParisTech.\n\nDownload slides\n\nAprès de plusieurs réformes de son cycle master (2A et 3A)\, Telecom Paristech [...]

A Markov point process for Fiber extraction\nBy Claire Coiffard\, IRMA\, Unistra.\n\n\nAbstract:\nThe aim of this work is to extract fibers in an image. We use a [...]

Social Sparsity: application to audio inpainting.\n\nBy Matthieu Kowalski\, L2S.\n\nAbstract:\nAudio inpainting problem is under consideration\, using iterative\nthresholding algorithms build on the "social sparsity" principle.\nFirst\, we present [...]

Bayesian approaches via sparsity enforcing priors for acoustic source imaging with robustness, super resolution and wide dynamic range. By Ning Chu, L2S. Acoustic imaging is [...]

Dictionary learning and application to EEG\n\nBy Quentin Barthelemy, CEA. This presentation addresses the issue of representing electroencephalographic (EEG) signals in an efficient way. While classical [...]

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 [...]

By Bob Sturm, Aalborg University Copenhagen. Abstract coming soon.

On the article "PhaseLift: Exact and Stable Signal Recovery from Magnitude Measurements via Convex Programming", Emmanuel J. Candès, Thomas Strohmer and Vladislav Voroninski see the [...]

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 [...]

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 [...]

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 [...]

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 [...]

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 [...]