Quick Overview


I am researcher (HDR) in

  • Machine Learning;
  • Statistics;
  • Signal Processing;


I am teaching at École des Ponts ParisTech.

  • Machine Learning;
  • Optimization;

Ph.D. Sutdents

  • Jiali MEI (2014-2017) with Jean-Marc Azaïs, Yannig Goude and Georges Hébrail; "Time series recovery and prediction with regression-enhanced nonnegative matrix factorization applied to electricity consumption" defended in December 2017.
  • Ernesto ARAYA (Started in 2017); Random Graphs.

Publications & Talks

Preprints/Papers can be found on HAL ArXiv

Statistics & Learning

  1. A Short Introduction to “Moment-SoS Hierarchies”, submitted, 2018.
  2. Minimax Adaptive Estimation of Nonparametric Geometric Graphs (with C. Lacour and T. M. Pham Ngoc), submitted, 2017.
  3. Approximate Optimal Designs for Multivariate Polynomial Regression (with F. Gamboa & D. Henrion & R. Hess & J.-B. Lasserre), Annals of Statistics, 2018 (to appear). Matlab Code
    Extended version of D-Optimal Design for Multivariate Polynomial Regression via the Christoffel function and Semidefinite Relaxations (with F. Gamboa & D. Henrion & R. Hess & J.-B. Lasserre), arXiv 1703.01777.
  4. Nonnegative Matrix Factorization with Side Information for Time Series Recovery and Prediction (with J-M Azaïs & Y. Goude & G. Hébrail & J. Mei), IEEE Transactions on Knowledge and Data Engineering, 2018 (to appear).
  5. Nonnegative Matrix Factorization for Time Series Recovery From a Few Temporal Aggregates (with J-M Azaïs & Y. Goude & G. Hébrail & J. Mei), Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2382-2390, 2017.
  6. Sparse Recovery from Extreme Eigenvalues Deviation Inequalities (with S. Dallaporta), ESAIM P&S, 2018 (to appear).
  7. Reconstructing undirected graphs from eigenspaces (with T. Espinasse & P. Rochet), Journal of Machine Learning Research, Volume 18, Issue 51, Pages 1−24, 2017.
  8. Power of the Spacing test for Least-Angle Regression (with J.-M. Azaïs & S. Mourareau), Bernoulli, Volume 24 n°1 (2018), Pages 465-492.
  9. Minimax adaptive estimation of non-parametric Hidden Markov Models (with É. Gassiat & C. Lacour), Journal of Machine Learning Research, Volume 17, Issue 111, Pages 1-43, 2016. Matlab Codes
  10. Randomized pick-freeze for sparse Sobol indices estimation in high dimension (with A. Janon), ESAIM P&S, Volume 19, 2015, Pages 725-745.
  11. Consistent estimation of the filtering and marginal smoothing distributions in nonparametric hidden Markov models (with É. Gassiat & S. Le Corff), IEEE Transactions on Information Theory, Volume 63, Issue 8, Aug. 2017, Pages 4758-4777.
  12. A Rice method proof of the Null-Space Property over the Grassmannian (with J.-M. Azaïs & S. Mourareau), Annales de l’Institut Henri Poincaré, Probabilités et Statistiques, Volume 53, Number 4 (2017), Pages 1821-1838.
  13. Estimating the transition matrix of a Markov chain observed at random times (with F. Barsotti, T. Espinasse & P. Rochet), Statistics & Probability Letters, Volume 94, November 2014, Pages 98-105.
  14. Optimal designs for Lasso and Dantzig selector using Expander Codes, IEEE Transactions on Information Theory, Volume 60, Issue 11, Nov. 2014, Pages 7293-7299.
  15. A remark on the lasso and the Dantzig selector, Statistics & Probability Letters, Volume 83, Issue 1, January 2013, Pages 304-314.

Inverse Problems

  1. On Representer Theorems and Convex Regularization (with C. Boyer, A. Chambolle, V. Duval, F. de Gournay & P. Weiss), arXiv 1806.09810. A related conference paper accepted to iTWIST'18 is Convex Regularization and Representer Theorems (with C. Boyer, A. Chambolle, V. Duval, F. de Gournay & P. Weiss).
  2. Testing Gaussian Process with Applications to Super-Resolution (with J.-M. Azaïs & S. Mourareau), Applied and Computational Harmonic Analysis (to appear). Python Code
  3. Adapting to Unknown Noise Level in Sparse Deconvolution (with C. Boyer & J. Salmon), Information & Inference: A Journal of the IMA, Volume 6, Issue 3, 1 September 2017, Pages 310–348.
  4. Exact solutions to Super Resolution on semi-algebraic domains in higher dimensions (with F. Gamboa & D. Henrion & J.-B. Lasserre), IEEE Transactions on Information Theory, Volume 63, Issue 1, Jan. 2017, Pages 621-630. Matlab Code
  5. Non-uniform spline recovery from small degree polynomial approximation (with G. Mijoule), Journal of Mathematical Analysis and Applications, Volume 430, Issue 2, 15 October 2015, Pages 971–992.
  6. Spike Detection from Inaccurate Samplings (with J.-M. Azaïs & F. Gamboa), Applied and Computational Harmonic Analysis, Volume 38, Issue 2, March 2015, Pages 177–195.
  7. Exact Reconstruction using Beurling Minimal Extrapolation (with F. Gamboa), Journal of Mathematical Analysis and Applications, Volume 395, Issue 1, Nov. 2012, Pages 336-354.
  8. Quantitative Isoperimetric Inequalities on the Real Line, Annales Mathématiques Blaise Pascal, Volume 18 n°2 (2011), Pages 311-331.


Jean-Marc Azaïs; Flavia Barsotti; Franck Barthe; Claire Boyer; Sandrine Dallaporta; Thibault Espinasse; Fabrice Gamboa; Élisabeth Gassiat; Yannig Goude; Georges Hébrail; Didier Henrion; Roxana Hess; Alexandre Janon; Claire Lacour; Jean-Bernard Lasserre; Sylvain Le Corff; Jiali Mei; Guillaume Mijoule; Stéphane Mourareau; Thanh Mai Pham Ngoc; Paul Rochet; Joseph Salmon;

Talks & Lectures

Talks are available at Speaker Deck


  • Séminaire d'Informatique de l'École Normale Supérieure, Lyon.
  • Séminaire de Probabilités de l'École Normale Supérieure, Lyon.
  • Groupe de Travail "Gaussian Process" Université Jean Monnet, St-Étienne.
  • Séminaire de Probabilités de Lille.
  • Séminaire de Probabilités et Statistique de Liège.
  • Séminaire de Probabilités et Statistique de Versailles, LMV.
  • Séminaire de Statistique de Toulouse, IMT.
  • Groupe de Travail "Sequential Structured Statistical Learning", IHES.
  • Cambridge Statistics Seminar, Cambridge, UK.
  • Séminaire de Probabilités de l'École Nationale Supérieure de Techniques Avancées, Palaiseau.
  • Séminaire de Probabilités et Statistique de Nanterre, Modal'X.
  • Séminaire de Probabilités de Rennes, IRMAR.
  • 2015 Saint Flour summer school.
  • Rencontres Statistique Lyonnaises.
  • Séminaire du CREST, ENSAE.




Since 2018 Senior Researcher at CERMICS
2017-2018 Invited Researcher at Inria Paris
2012-2018 Maître de Conférences Habilité at Institut de Mathématique d'Orsay H.D.R
2008-2012 Ph.D. at Institut de Mathématiques de Toulouse Ph.D. Thesis
2004-2009 Student at École Normale Supérieure


  • yohann.de-castro@enpc.fr
  • (000) 000-0000
  • Office B215 in Coriolis Building
    École des Ponts ParisTech
    FR 77455 Marne la Vallée Cedex 2