Evgenii Chzhen

Orcid: 0009-0003-3065-4267

According to our database1, Evgenii Chzhen authored at least 14 papers between 2017 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2025
Narrowing the Gap between Adversarial and Stochastic MDPs via Policy Optimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024
Regression under demographic parity constraints via unlabeled post-processing.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Addressing Bias in Online Selection with Limited Budget of Comparisons.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023
Small Total-Cost Constraints in Contextual Bandits with Knapsacks, with Application to Fairness.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fair learning with Wasserstein barycenters for non-decomposable performance measures.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
A gradient estimator via L1-randomization for online zero-order optimization with two point feedback.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Set-valued classification - overview via a unified framework.
CoRR, 2021

Classification with abstention but without disparities.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

A Unified Approach to Fair Online Learning via Blackwell Approachability.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
An example of prediction which complies with Demographic Parity and equalizes group-wise risks in the context of regression.
CoRR, 2020

Fair regression via plug-in estimator and recalibration with statistical guarantees.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Fair regression with Wasserstein barycenters.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2017
On the benefits of output sparsity for multi-label classification.
CoRR, 2017


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