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Séminaire IMAGE : Quentin Bertrand (MILA), « Hyperparameter selection for high dimensional sparse learning: application to neuro-imaging »
Séminaire IMAGE : Quentin Bertrand (MILA), « Hyperparameter selection for high dimensional sparse learning: application to neuro-imaging »
Speaker: Quentin Bertrand (https://qb3.github.io/) Abstract: Due to non-invasiveness and excellent time resolution, magneto- and electroencephalography (M/EEG) have emerged as tools of choice to monitor brain activity. Reconstructing brain signals from M/EEG measurements is a high dimensional ill-posed inverse problem. Typical estimators of brain signals involve challenging optimization problems, composed of the sum of a data-fidelity … Continue reading Séminaire IMAGE : Quentin Bertrand (MILA), « Hyperparameter selection for high dimensional sparse learning: application to neuro-imaging »
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