Narrowing the gap between adversarial and stochastic MDPs via policy optimization
D. Tiapkin, E. Chzhen, G. Stoltz
AISTATS 2025
Regression under demographic parity constraints via unlabeled post-processing
E. Chzhen, M. Hebiri, G. Taturyan
NeurIPS 2024
Addressing bias in online selection with limited budget of comparisons
Z. Benomar, E. Chzhen, N. Schreuder, V. Perchet
NeurIPS 2024
Gradient free optimization of highly smooth functions
A. Akhavan, E. Chzhen, M. Pontil, A. Tsybakov
Journal of Machine Learning Research 2024
Parameter-free projected gradient descent
E. Chzhen, C. Giraud, G. Stoltz
Preprint 2023
Small Total-Cost Constraints in Contextual Bandits with Knapsacks, with Application to Fairness
E. Chzhen, C. Giraud, Z. Li, G. Stoltz
NeurIPS 2023
SignSVRG: fixing SignSGD via variance reduction
E. Chzhen, S. Schechtman
Preprint 2023
Fair learning with Wasserstein barycenters for non-decomposable performance measures
S. Gaucher, N. Schreuder, E. Chzhen
AISTATS 2023
A minimax framework for quantifying risk-fairness trade-off in regression
E. Chzhen, N. Schreuder
Annals of Statistics 2022
A gradient estimator via L1-randomization for online zero-order optimization with two point feedback
A. Akhavan, E. Chzhen, M. Pontil, A. Tsybakov
NeurIPS 2022 (spotlight, code)
A unified approach to fair online learning via Blackwell approachability
E. Chzhen, C. Giraud, G. Stoltz
NeurIPS 2021 (spotlight)
Set-valued classification -- overview via a unified framework
E. Chzhen, C. Denis, M. Hebiri, T, Lorieul
Preprint 2021
Classification with abstention but without disparities
N. Schreuder, E. Chzhen
UAI 2021 (spotlight, code)
Minimax semi-supervised set-valued approach to multi-class classification
E. Chzhen, C. Denis, M. Hebiri
Bernoulli 2021 (code)
Optimal Rates for Nonparametric F-Score Binary Classification via Post-Processing
E. Chzhen
Mathematical Methods of Statistics 2021
An example of prediction which complies with Demographic Parity and equalizes group-wise risks in the context of regression
E. Chzhen, N. Schreuder
AFCI at NeurIPS 2020
Fair regression with wasserstein barycenters
E. Chzhen, C. Denis, M. Hebiri, L. Oneto, M. Pontil
NeurIPS 2020 (code)
Fair Regression via Plug-in Estimator and Recalibration With Statistical Guarantees
E. Chzhen, C. Denis, M. Hebiri, L. Oneto, M. Pontil
NeurIPS 2020 (oral, code)
Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification
E. Chzhen, C. Denis, M. Hebiri, L. Oneto, M. Pontil
NeurIPS 2019
On Lasso refitting strategies
E. Chzhen, M. Hebiri, J. Salmon
Bernoulli 2019
Plug-in methods in classification
E. Chzhen
PhD manuscript 2019
Classification of sparse binary vectors
E. Chzhen
Technical Report 2019
On the benefits of output sparsity for multi-label classification
E. Chzhen, C. Denis, M. Hebiri, J. Salmon
Technical Report 2017