Mathematics of decision making and statistics

Jérôme Bolte, Camille Castera, Edouard Pauwels, and Cédric Févotte, “An Inertial Newton Algorithm for Deep Learning”, TSE Working Paper, n. 19-1043, October 2019.

Jérôme Bolte, and Edouard Pauwels, “Conservative set valued fields, automatic differentiation, stochastic gradient methods and deep learning”, TSE Working Paper, n. 19-1044, October 2019.

Fabien Gensbittel, “Continuous-Time Markov Games with Asymmetric Information”, Dynamic Games and Applications, vol. 9, n. 3, September 2019, pp. 671–699.

Y. De Castro, Sébastien Gadat, Clément Marteau, and Cathy Maugis, “SuperMix: Sparse Regularization for Mixture”, TSE Working Paper, n. 19-1040, September 2019, revised September 2020.

Olivier Faugeras, and Ludger Rüschendorf, “Functional, randomized and smoothed multivariate quantile regions”, TSE Working Paper, n. 19-1039, September 2019, revised June 2021.

Laurent Miclo, “On the Markov commutator”, Bulletin des Sciences Mathématiques , vol. 154, August 2019, pp. 1–35.

Michel Simioni, Christine Thomas-Agnan, and Thi-Huong Trinh, “Relations between socio-economic factors and nutritional diet in Vietnam from 2004 to 2014: New insights using compositional data analysis”, Statistical Methods in Medical Research Journal, vol. 28, n. 8, August 2019, pp. 2305–2325.

Jad Beyhum, “Inference robust to outliers with L1‐norm penalization”, TSE Working Paper, n. 19-1032, August 2019.

Abdelaati Daouia, and Davy Paindaveine, “Multivariate Expectiles, Expectile Depth and Multiple-Output Expectile Regression”, TSE Working Paper, n. 19-1022, July 2019, revised February 2023.

Christophe Gaillac, and Eric Gautier, “Adaptive estimation in the linear random coefficients model when regressors have limited variation”, TSE Working Paper, n. 19-1026, July 2019.