Pierre Humbert
Postdoc in probability and statistics
Since September 2021, I am a postdoc in the probability and statistics team of the Laboratoire de Mathématiques d'Orsay (LMO) with Sylvain Arlot. I am also a member of the INRIA Celeste team.
Before that, I completed a PhD at ENS Paris-Saclay entitled Multivariate analysis with tensors and graphs - application to neuroscience, under the supervision of Nicolas Vayatis, Laurent Oudre, and Julien Audiffren.
CV is available here .
Main research interests
- Statistical learning, non-parametric statistics
- Conformal prediction, cross-validation
- Robust statistics
- Signal processing
- Graph and tensor learning
- Applications to neuroscience

Contact
Département de Mathématiques
Bâtiment 307
Faculté des Sciences d'Orsay
Université Paris-Saclay
91405 Orsay Cedex
France
Office : 2F3
+33 1 69 15 60 28
prenom.nom@universite-paris-saclay.fr
Main publications
Journals
- (2021) P. Humbert*, B. Le Bars*, L. Oudre, A. Kalogeratos, N. Vayatis. Learning Laplacian matrix from graph signals with sparse spectral representation
Journal of Machine Learning Research (JMLR). [journal] [pdf] [code] - (2021) P. Humbert, L. Oudre, N. Vayatis, J. Audiffren. Tensor convolutional dictionary learning with CP low-rank activations
IEEE Transactions on Signal Processing (TSP). [journal] [pdf] [code] - (2019) P. Humbert, C. Dubost, J. Audiffren, L. Oudre. Apprenticeship learning for a predictive state representation of anesthesia
IEEE Transactions on Biomedical Engineering (TBME). [journal] [pdf]
Conferences
- (2023) P. Humbert, B. Le Bars, A. Bellet, S. Arlot. One-shot federated conformal prediction
International Conference on Machine Learning (ICML), 2023. [hal] [pdf] [code]
- (2022) P. Humbert*, B. Le Bars*, L. Minvielle*. Robust kernel density estimation with median-of-means principle
International Conference on Machine Learning (ICML), 2022. [conference] [pdf] [code] - (2021) P. Humbert, L. Oudre, C. Dubost. Learning spatial filters from EEG signals with graph signal processing methods
IEEE Engineering in Medecine and Biology Society (EMBC), 2021. [pdf] - (2021) T. Gnassounou, P. Humbert, L. Oudre. Adaptive subsampling of multidomain signals with graph products
International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2021. [conference] [pdf] [code] - (2020) B. Le Bars, P. Humbert, A. Kalogeratos, N. Vayatis. Learning the piece-wise constant graph structure of a varying Ising model
International Conference on Machine Learning (ICML), 2020. [conference] [pdf] [code] - (2020) P. Humbert, J. Audiffren, L. Oudre, N. Vayatis. Low rank activations for tensor-based convolutional sparse coding
International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020. [conference] [pdf] [code] - (2019) P. Humbert, L. Oudre, N. Vayatis. Subsampling of multivariate time-vertex graph signals
European Signal Processing Conference (EUSIPCO), 2019. [conference] - (2019) B. Le Bars*, P. Humbert*, L. Oudre, A. Kalogeratos. Learning Laplacian matrix from bandlimited graph signals
International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019. [conference] [pdf] [code]