“Statistical learning with high-cardinality string categorical variables »
Gaël Varoquaux, Inria (team Parietal), Palaiseau, France.
Laurent Charlin, HEC Montréal, Montréal, Canada.
Stéphane Gaïffas, Université Paris Diderot (LPSM), Paris, France.
Balázs Kégl, Huawei/CNRS, France.
Charles Bouveyron, Université Côte d’Azur, Nice, France.
Marc Schoenauer, Inria (team TAU), France.
Patrick Valduriez, Inria (LIRMM), Montpellier, France.
Wonderful work presented by Jerome for his PhD defense : the first predictive meta-analysis of neuroimaging publications.
Congratulations to Jerome, and his supervisors, Gael Varoquaux and Fabian Suchanek.
We are pleased to share the good news that four papers out of four submissions from our team have been accepted for NeurIPS 2019 (alphab. order):
1) Pierre Ablin, T. Moreau, M. Massias & A. Gramfort: “Learning step sizes for unfolded sparse coding” https://arxiv.org/abs/1905.11071
2) Quentin Bertrand, M. Messias, A. Gramfort and J. Salmon: “Concomitant Lasso with Repetitions (CLaR): beyond averaging multiple realizations of heteroscedastic noise” https://arxiv.org/abs/1902.02509
3) David Sabbagh, P. Ablin, G. Varoquaux, A. Gramfort and D. Engemann: “Manifold-regression to predict from MEG/EEG brain signals without source modeling” https://arxiv.org/abs/1906.02687
4) Meyer Scetbon & G. Varoquaux A: “Comparing distributions: l1 geometry improves kernel two-sample testing” (selected as spotlight).
See you in Vancouver!
Big colloquium at Collège de France on April 23, 2019, co-organized by B.Thirion, will feature P. Ciuciu and O.Grisel. Here is more information:
High-performance Simulation for the design of compressed sensing trajectories in high resolution functional neuroimaging at 7 and 11.7 Tesla.
For the reconstruction part, the slides are here: