I am a third year PhD student in Statistics at CREST (Center for Research in Economics and Statistics), (near) Paris, supervised by Arnak Dalalyan.
I am mainly interested in statistical learning theory, high-dimensional statistics and fair learning. I co-organize the Stat·Eco·ML bi-monthly seminar at CREST.
- Nicolas Schreuder, Evgenii Chzhen (2021). Classification with abstention but without disparities. Submitted.
- Nicolas Schreuder, Victor-Emmanuel Brunel, Arnak Dalalyan (2020). Statistical guarantees for generative models without domination. ALT 2021.
- Evgenii Chzhen, Nicolas Schreuder (2020). A minimax framework for quantifying risk-fairness trade-off in regression. Submitted.
- Evgenii Chzhen, Nicolas Schreuder (2020). An example of prediction which complies with Demographic Parity and equalizes group-wise risks in the context of regression. NeurIPS 2020 Workshop on Algorithmic Fairness through the Lens of Causality and Interpretability.
- Nicolas Schreuder (2020). Bounding the expectation of the supremum of empirical processes indexed by Hölder classes. To appear in Mathematical Methods of Statistics.
- Nicolas Schreuder, Victor-Emmanuel Brunel, Arnak Dalalyan (2019). A nonasymptotic law of iterated logarithm for general M-estimators. AISTATS 2020.
Teaching (at ENSAE Paris)
- Numerical Analysis and Numerical Linear Algebra with S. M. Kaber.
- Applied Statistics Project with J. Depersin.
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