Nikita Yurevich Kotelevskii — accepted AI-conference papers

2022

FedPop: A Bayesian Approach for Personalised Federated Learning

Nikita Yurevich Kotelevskii, Maxime Vono, Alain Durmus, Eric Moulines

NeurIPS 2022accept

Personalised federated learning (FL) aims at collaboratively learning a machine learning model tailored for each client. Albeit promising advances have been made in this direction, most of the existing approaches do not allow for uncertainty quantification which is crucial in many applications. In a…

Cited by 39 Source ↗PDF ↗Scholar ↗

2022

Nonparametric Uncertainty Quantification for Single Deterministic Neural Network

Nikita Yurevich Kotelevskii, Aleksandr Artemenkov, Kirill Fedyanin, Fedor Noskov, Alexander Fishkov, Artem Shelmanov +3

NeurIPS 2022accept

This paper proposes a fast and scalable method for uncertainty quantification of machine learning models' predictions. First, we show the principled way to measure the uncertainty of predictions for a classifier based on Nadaraya-Watson's nonparametric estimate of the conditional label distribution.…

Cited by 32 Source ↗PDF ↗code ↗Scholar ↗