On the benefits of output sparsity for multi-label classification. - Evgenii Chzhen; Christophe Denis; Mohamed Hebiri; Joseph Salmon (CoRR, 2017)

Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification. - Evgenii Chzhen; Christophe Denis; Mohamed Hebiri; Luca Oneto; Massimiliano Pontil (NeurIPS, 2019)

Fair regression with Wasserstein barycenters. - Evgenii Chzhen; Christophe Denis; Mohamed Hebiri; Luca Oneto; Massimiliano Pontil (NeurIPS, 2020)

Fair regression via plug-in estimator and recalibration with statistical guarantees. - Evgenii Chzhen; Christophe Denis; Mohamed Hebiri; Luca Oneto; Massimiliano Pontil (NeurIPS, 2020)

An example of prediction which complies with Demographic Parity and equalizes group-wise risks in the context of regression. - Evgenii Chzhen; Nicolas Schreuder (CoRR, 2020)

A Unified Approach to Fair Online Learning via Blackwell Approachability. - Evgenii Chzhen; Christophe Giraud 002; Gilles Stoltz (NeurIPS, 2021)

Classification with abstention but without disparities. - Nicolas Schreuder; Evgenii Chzhen (UAI, 2021)

Set-valued classification - overview via a unified framework. - Evgenii Chzhen; Christophe Denis; Mohamed Hebiri; Titouan Lorieul (CoRR, 2021)

A gradient estimator via L1-randomization for online zero-order optimization with two point feedback. - Arya Akhavan; Evgenii Chzhen; Massimiliano Pontil; Alexandre B. Tsybakov (NeurIPS, 2022)

Fair learning with Wasserstein barycenters for non-decomposable performance measures. - Solenne Gaucher; Nicolas Schreuder; Evgenii Chzhen (AISTATS, 2023)

Small Total-Cost Constraints in Contextual Bandits with Knapsacks, with Application to Fairness. - Evgenii Chzhen; Christophe Giraud 002; Zhen Li; Gilles Stoltz (NeurIPS, 2023)

Addressing Bias in Online Selection with Limited Budget of Comparisons. - Ziyad Benomar; Evgenii Chzhen; Nicolas Schreuder; Vianney Perchet (NeurIPS, 2024)

Regression under demographic parity constraints via unlabeled post-processing. - Gayane Taturyan; Evgenii Chzhen; Mohamed Hebiri (NeurIPS, 2024)

Narrowing the Gap between Adversarial and Stochastic MDPs via Policy Optimization. - Daniil Tiapkin; Evgenii Chzhen; Gilles Stoltz (AISTATS, 2025)