Thematic team Statistics, data, algorithms

## Statistics seminar

#### Day, hour and place

Tuesday at 09:30, Sophie Germain en salle 1013 / Jussieu en salle 15-16.201

#### Contact(s)

### Next talks

Statistics seminar

Friday December 8, 2023, 9:30AM, Jussieu en salle 16-26-209

**Pierre Alquier** (ESSEC) *Robust estimation and regression with MMD*

In the second part of this talk, I will discuss the extension of this method to the estimation of conditional distributions, which allows to use MMD-estimators in various regression models. On the contrary to mean embeddings, very technical conditions are required for the existence of a conditional mean embedding that allows defining an estimator. In most papers, these conditions are often assumed, but rarely checked. It turns out that, in most generalized linear regression models, we proved that these conditions can be met, at the cost of more restrictions on the kernel choice.

This is based on joint works with: Badr-Eddine Chérief-Abdellatif (CNRS, Paris), Mathieu Gerber (University of Bristol), Daniele Durante (Bocconi University), Sirio Legramanti (University of Bergamo), Jean-David Fermanian (ENSAE Paris), Alexis Derumigny (TU Delft), Geoffrey Wolfer (RIKEN-AIP, Tokyo).

Statistics seminar

Tuesday January 23, 2024, 9:30AM, Jussieu en salle 15-16.201

**Chiara Amorino** (University of Luxembourg) *To be announced.*

Statistics seminar

Tuesday January 30, 2024, 9:30AM, Jussieu en salle 15-16.201

**Ester Mariucci** (Université Versailles Saint Quentin) *To be announced.*

To add the talks calendar to your agenda, subscribe to this calendar by using this link.

### Previous talks

#### Year 2023

Statistics seminar

Tuesday November 21, 2023, 9:30AM, Jussieu en salle 15-16.201

**Deborah Sulem** (Barcelona School of Economics / Universitat Pompeu Fabra) *Bayesian inference for multivariate event data with dependence*

Statistics seminar

Tuesday November 7, 2023, 9:30AM, Jussieu en salle 15-16.201

**Alberto Suarez** (Universidad Autónoma de Madrid) *The arrow of time: at the intersection of thermodynamics, machine learning, and causality*

Statistics seminar

Tuesday October 10, 2023, 9:30AM, Jussieu en salle 15-16.201

**Paul Escande** *On the Concentration of the Minimizers of Empirical Risks*

Instead of deriving guarantees on the usual estimation error, we will explore concentration inequalities on the distance between the sets of minimizers of the risks. We will argue that for a broad spectrum of estimation problems, there exists a regime where optimal concentration rates can be proven. The bounds will be showcased on a selection of estimation problems such as barycenters on metric space with positive or negative curvature, subspaces of covariance matrices, regression problems and entropic-Wasserstein barycenters.

Statistics seminar

Thursday September 28, 2023, 9:30AM, Jussieu en salle 15-25.102

**Ruth Heller** (Tel-Aviv University) *Simultaneous Directional Inference*

The relevant paper is arXiv:2301.01653 Joint work with Aldo Solari

Statistics seminar

Tuesday May 30, 2023, 9:30AM, Jussieu en salle 15-16.201

**Michael Arbel** (INRIA) *Non-Convex Bilevel Games with Critical Point Selection Maps*

Statistics seminar

Thursday May 25, 2023, 9:30AM, Jussieu en salle 15-16.201

**Jeffrey Näf** (INRIA Montpellier) *Distributional Random Forest: Heterogeneity Adjustment and Multivariate Distributional Regression*

Statistics seminar

Tuesday May 23, 2023, 9:30AM, Jussieu en salle 15-16.201

**Evguenii Chzhen** (Orsay) *Demographic parity constraint for algorithmic fairness : a statistical perspective*

This talk is based on a sequence of joint works with Ch. Denis, S. Gaucher, M. Hebiri, L. Oneto, M. Pontil, and N. Schreuder.

Statistics seminar

Tuesday May 9, 2023, 9:30AM, Jussieu en salle 15-16.201

**Charlotte Dion-Blanc** (Sorbonne Université) *Classification multi-classes, pour des trajectoires issues de processus de diffusions*

Statistics seminar

Tuesday April 11, 2023, 9:30AM, Sophie Germain en salle 1013

**Tabea Rebafka** (Sorbonne Université) *Model-based graph clustering with an application to ecological networks*

Statistics seminar

Tuesday March 28, 2023, 9:30AM, Jussieu en salle 15-16.201

**David Rossell** (Universitat Pompeu Fabra) *Statistical inference with external information: high-dimensional data integration*

Statistics seminar

Tuesday March 21, 2023, 9:30AM, Sophie Germain en salle 1013

**Cécile Durot** (Université Paris Nanterre) *To be announced.*

Statistics seminar

Thursday March 9, 2023, 9:30AM, Jussieu en salle 16-26.209

**Pierre Wolinski** (INRIA) *Gaussian Pre-Activations in Neural Networks: Myth or Reality?*

Statistics seminar

Thursday February 9, 2023, 9:30AM, Sophie Germain en salle 1016

**Vincent Divol** (CEREMADE) *Estimation d'applications de transport optimal dans des espaces fonctionnels généraux*

Statistics seminar

Tuesday January 24, 2023, 9:30AM, Jussieu en salle 15-16.201

**Laure Sansonnet** (INRAE MIA Paris-Saclay) *Sélection de variables dans des modèles linéaires (généralisés) multivariés avec dépendance*

La première partie est en collaboration avec Julien Chiquet, Céline Lévy-Leduc et Marie Perrot-Dockès et la deuxième partie est en collaboration avec Marina Gomtsyan, Céline Lévy-Leduc et Sarah Ouadah.

#### Year 2022

Statistics seminar

Tuesday December 6, 2022, 9:30AM, Jussieu en salle 15-16.201

**Vianney Perchet** (ENSAE) *An algorithmic solution to the Blotto game using multi-marginal couplings*

Statistics seminar

Tuesday November 22, 2022, 9:30AM, Sophie Germain en salle 1013 / Jussieu en salle 15-16.201

**Morgane Austern** (Harvard University) *To split or not to split that is the question: From cross validation to debiased machine learning.*

Statistics seminar

Tuesday November 8, 2022, 9:30AM, Jussieu en salle 15-16.201

**Arshak Minasyan** (CREST-ENSAE) *All-In-One Robust Estimator of sub-Gaussian Mean*

Statistics seminar

Thursday October 20, 2022, 11AM, Jussieu en salle 15-16.201

**Misha Belkin** (University of California) *Neural networks, wide and deep, singular kernels and Bayes optimality*

Statistics seminar

Tuesday October 11, 2022, 9:30AM, Jussieu en salle 15-16.201 et retransmission

**Yifan Cui** (Zhejiang University) *Instrumental Variable Approaches To Individualized Treatment Regimes Under A Counterfactual World*

Statistics seminar

Tuesday September 27, 2022, 9:30AM, Jussieu en salle 15-16.201

**Emilie Kaufmann** (CNRS) *Exploration non paramétrique dans les modèles de bandits*

Statistics seminar

Tuesday May 31, 2022, 9:30AM, Sophie Germain en salle 1013 / Jussieu en salle 15-16.201

**Elsa Cazelles** (IRIT) *A novel notion of barycenter for probability distributions based on optimal weak mass transport*

Statistics seminar

Tuesday May 10, 2022, 9:30AM, Sophie Germain en salle 1013 / Jussieu en salle 15-16.201

**Guillaume Lecué** (CREST) *A geometrical viewpoint on the benign overfitting property of the minimum $\ell_2$-norm interpolant estimator.*

[1] Mikhail Belkin, Daniel Hsu, Siyuan Ma, and Soumik Mandal. Reconciling modern machine-learning practice and the classical bias-variance trade-off. Proc. Natl. Acad. Sci. USA, 116(32):15849–15854, 2019.

[2] Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, and Oriol Vinyals. Understanding deep learning (still) requires rethinking generalization. Commun. ACM, 64(3):107–115, 2021.

[3] Peter L. Bartlett, Philip M. Long, Gabor Lugosi, and Alexander Tsigler. Benign overfitting in linear regression. Proc. Natl. Acad. Sci. USA, 117(48):30063–30070, 2020.

[4] Peter L. Bartlett, Andreas Montanari, and Alexander Rakhlin. Deep learning: a statistical viewpoint. To appear in Acta Numerica, 2021.

[5] Mikhail Belkin. Fit without fear: remarkable mathematical phenomena of deep learning through the prism of interpolation. To appear in Acta Numerica, 2021.

[6] Alexander Tsigler and Peter L. Bartlett. Benign overfitting in ridge regression. 2021.

Statistics seminar

Tuesday April 19, 2022, 9:30AM, Sophie Germain en salle 1013 / Jussieu en salle 15-16.201

**Clément Marteau** (Université Lyon 1) *Supermix : régularisation parcimonieuse pour des modèles de mélange*

Statistics seminar

Tuesday April 5, 2022, 9:30AM, Sophie Germain en salle 1013 / Jussieu en salle 15-16.201

**Fabrice Grela** (Université de Nantes) *Minimax detection and localisation of an abrupt change in a Poisson process*

Statistics seminar

Tuesday March 22, 2022, 9:30AM, Sophie Germain en salle 1013 / Jussieu en salle 15-16.201

**Aymeric Dieuleveut** (Polytechnique) *Federated Learning and optimization: from a gentle introduction to recent results*

Refs:Mainly: Differentially Private Federated Learning on Heterogeneous Data, M Noble, A Bellet, A Dieuleveut, Aistats 2022, Link Preserved central model for faster bidirectional compression in distributed settings C Philippenko, A Dieuleveut, Neurips 2021 LinkIf time allows it (unlikely): Federated Expectation Maximization with heterogeneity mitigation and variance reduction, A Dieuleveut, G Fort, E Moulines, G Robin, Neurips 2021 Link

Statistics seminar

Tuesday March 8, 2022, 9:30AM, Sophie Germain en salle 1013 / Jussieu en salle 15-16.201

**Lihua Lei** (Stanford University) *Testing for outliers with conformal p-values*

Statistics seminar

Tuesday February 8, 2022, 9:30AM, Sophie Germain en salle 1013 / Jussieu en salle 15-16.201

**Élisabeth Gassiat** *Deconvolution with unknown noise distribution*

Statistics seminar

Tuesday January 25, 2022, 9:30AM, Sophie Germain en salle 1013 / Jussieu en salle 15-16.201

**Nicolas Verzelen** (Université de Montpellier) *Optimal ranking in crowd-sourcing problem*

This talk is based on a joint ongoing work with Alexandra Carpentier and Emmanuel Pilliat.

#### Year 2021

Statistics seminar

Tuesday December 14, 2021, 9:30AM, Sophie Germain en salle 1013 / Jussieu en salle 15-16.201

**Julie Delon** (Université de Paris) *Some perspectives on stochastic models for Bayesian image restoration*

Statistics seminar

Tuesday November 30, 2021, 9:30AM, Sophie Germain en salle 1013 / Jussieu en salle 15-16.201

**Frédéric Chazal** (INRIA) *A framework to differentiate persistent homology with applications in Machine Learning and Statistics*

However, the approaches proposed in the literature are usually

anchored to a specific application and/or topological construction, and do not come with theoretical guarantees.

In this talk, we will study the differentiability of a general map associated with the most common topological construction, that is, the persistence map. Building on real analytic geometry arguments, we propose a general framework that allows to define and compute gradients for persistence-based functions in a very simple way. As an application, we also provide a simple, explicit and sufficient condition for convergence of stochastic subgradient methods for such functions. If time permits, as another application, we will also show how this framework combined with standard geometric measure theory arguments leads to results on the statistical behavior of persistence diagrams of filtrations built on top of random point clouds.

Statistics seminar

Tuesday November 23, 2021, 9:30AM, Sophie Germain en salle 1013 / Jussieu en salle 15-16.201

**Yannick Baraud** (Université de Luxembourg) *Comment construire des lois a posteriori robustes à partir de tests ?*

Statistics seminar

Tuesday November 9, 2021, 9:30AM, Sophie Germain en salle 1013 / Jussieu en salle 15-16.201

**Alessandro Rudi** (INRIA) *PSD models for Non-convex optimization and beyond*

Statistics seminar

Tuesday October 19, 2021, 9:30AM, Sophie Germain en salle 1013

**Antoine Marchina** (Université de Paris) *Concentration inequalities for suprema of unbounded empirical processes*

Statistics seminar

Tuesday October 5, 2021, 9:30AM, Jussieu en salle 15-16.201

**Judith Rousseau** (Oxford) *Semiparametric and nonparametric Bayesian inference in hidden Markov models*

Joint work with D. Moss (Oxford).