Gradient-free optimization of highly smooth functions

A. Akhavan, E. Chzhen, M. Pontil, A. Tsybakov

Preprint 2023

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

Addressing bias in online selection with limited budget of comparisons

Z. Benomar, E. Chzhen, N. Schreuder, V. Perchet

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