no code implementations • NAACL 2021 • Alexey Drutsa, Dmitry Ustalov, Valentina Fedorova, Olga Megorskaya, Daria Baidakova
In this tutorial, we present a portion of unique industry experience in efficient natural language data annotation via crowdsourcing shared by both leading researchers and engineers from Yandex.
no code implementations • 20 Jun 2019 • Valentina Fedorova, Gleb Gusev, Pavel Serdyukov
We study the problem of aggregation noisy labels.
no code implementations • 9 Jun 2019 • Nadezhda Bugakova, Valentina Fedorova, Gleb Gusev, Alexey Drutsa
Answers to pairwise tasks are known to be affected by the position of items on the screen, however, previous models for aggregation of pairwise comparisons do not focus on modeling such kind of biases.
no code implementations • 14 Mar 2016 • Vladimir Vovk, Ilia Nouretdinov, Valentina Fedorova, Ivan Petej, Alex Gammerman
We study optimal conformity measures for various criteria of efficiency of classification in an idealised setting.
1 code implementation • NeurIPS 2015 • Vladimir Vovk, Ivan Petej, Valentina Fedorova
This paper studies theoretically and empirically a method of turning machine-learning algorithms into probabilistic predictors that automatically enjoys a property of validity (perfect calibration) and is computationally efficient.
no code implementations • 21 Jun 2014 • Vladimir Vovk, Ivan Petej, Valentina Fedorova
This paper proposes a new method of probabilistic prediction, which is based on conformal prediction.