I am a postdoctoral fellow at CREST, ENSAE, in the group FairPlay, under the supervision of Vianney Perchet. This post-doc is funded by an Hadamard postdoctoral fellowship.

I am mainly interested in sequential learning and sequential decision-making problems, and in fair machine learning.

Papers, preprints, and software

Demographic parity in regression and classification within the unawareness framework (2024) V. Divol and S. Gaucher. Preprint

Improved Algorithms for Contextual Dynamic Pricing (2024) M. Tullii, S. Gaucher, N. Merlis and V. Perchet. Preprint

Feature-Based Online Bilateral Trade (2024) S. Gaucher, M. Bernasconi, M. Castiglioni, A. Celli and V. Perchet. Preprint

Supervised Contamination Detection, with Flow Cytometry Application (2024) S. Gaucher, G. Blanchard, and F.Chazal. Preprint

Position Paper: Open Research Challenges for Private Advertising Systems under Local Differential Privacy (2024) M. Tullii, S. Gaucher, H. Richard, E. Diemert, V. Perchet, A. Rakotomamonjy, C. Calauzènes, and M. Vono. Preprint

Fair learning with Wasserstein barycenters for non-decomposable performance measures (2023) S. Gaucher, N. Schreuder, and E. Chzhen. AISTATS 2023. Paper

The price of unfairness in linear bandits with biased feedback (2022), S. Gaucher, A. Carpentier, and C. Giraud. NeurIPS 2022. Preprint on Hall, Short Presentation

Hierarchical transfer learning with applications for electricity load forecasting (2021), A. Antoniadis, S. Gaucher, and Y. Goude.To appear in International Journal of Forecasting. Preprint on HAL

Maximum Likelihood Estimation of Sparse Networks with Missing Observations, S. Gaucher, O. Klopp (2021). Journal of Statistical Planning and Inference, Preprint on HAL

Outliers Detection in Networks with Missing Links, S. Gaucher, O. Klopp, G. Robin (2021). Computational Statistics and Data Analysis.Preprint on Arxiv

Optimality of Variational Inference for Stochastic Block Model with Missing Links, S. Gaucher, O. Klopp (2021). NeuRIPS 2021

Finite Continuum-Armed Bandits (2020), S. Gaucher. NeuRIPS 2020, Short Presentation, Poster

R package gsbm (2020). S Gaucher, G. Robin. The package allows to robustly estimate probabilities of connections in the presence of missing observations and outlier nodes, while detecting those outlier nodes.

Teaching

Online Leaning and Aggregation, 3rd year students, ENSAE, Link

Past teaching

Rappels de Statistiques Mathématiques, Master Spécialisé, ENSAE, 2018-2019. Link to the page of the course.

Introduction to Machine Learning, 2nd year students, ENSAE, 2019-2020. Link to the page of the course.

Statistiques 1, 2nd year students, ENSAE, 2018-2020. Link to the page of the course.

Selected talks and posters

Fair classification under demographic parity, Feb. 2024, Institut für Mathematik, Universität Potsdam.

Relationship between fair classification and fair regression, Dec. 2023, Meeting in Mathematical Statistics - CIRM. video

The price of unfairness in linear bandits with biased feedback, July 27th, 2023, ELLIS unConference, HEC, Jouy-en-Josas.

Introduction to Algorithmic Fairness, June 2023, mini-courses for the DataShape seminar, Porquerolles.

The price of unfairness in linear bandits with biased feedback, May 17th, 2022, workshop “Re-thinking High-dimensional Mathematical Statistics”, Mathematisches Forschungsinstitut Oberwolfach, Oberwolfach.

An Introduction to Continuum-armed Bandits with extension to the finite setting, Novembre 23rd, 2021, Institut für Mathematik, Potsdam.

Robust estimation in network with outliers and missing links, Octobre 21st, MAD-STAT seminar, Toulouse School of Economics.

Outliers Detection in Networks with Missing Links, July 8th, 2021, “Data Science, Statistics & Visualisation and European Conference on Data Analysis 2021”

Continuum-armed bandits : from the classical setting to the finite setting, April 6th, 2021, Seminaire Palaisien, Palaiseau.

Introduction to Stochastic Bandits, March 17th, 2021, StatEcoML Seminar, Palaiseau.

Robust Link Prediction in the Stochastic Block Model, October 23. 2019, Network Days III, Orsay.

Maximum Likelihood Estimation of Sparse Networks with Missing Observations, April 5. 2019, Huitièmes Rencontres des Jeunes Statisticiens, Hyères.

Estimation of Sparse Networks, October 25. 2018, Network Days II, Orsay.