Self-training: A survey MR Amini, V Feofanov, L Pauletto, L Hadjadj, E Devijver, Y Maximov arXiv preprint arXiv:2202.12040, 2022 | 100 | 2022 |
Importance sampling the union of rare events with an application to power systems analysis AB Owen, Y Maximov, M Chertkov | 56 | 2019 |
Searching equillibriums in Beckmann's and Nesterov--de Palma's models A Gasnikov, P Dvurechensky, Y Dorn, Y Maximov arXiv preprint arXiv:1506.00293, 2015 | 49* | 2015 |
Rademacher complexity bounds for a penalized multi-class semi-supervised algorithm Y Maximov, MR Amini, Z Harchaoui Journal of Artificial Intelligence Research 61, 761-786, 2018 | 42 | 2018 |
Efficient numerical algorithms for regularized regression problem with applications to traffic matrix estimations A Anikin, P Dvurechensky, A Gasnikov, A Golov, A Gornov, Y Maximov, ... arXiv preprint arXiv:1508.00858, 2015 | 41* | 2015 |
User preference and embedding learning with implicit feedback for recommender systems S Sidana, M Trofimov, O Horodnytskyi, C Laclau, Y Maximov, MR Amini Data Mining and Knowledge Discovery 35, 568-592, 2021 | 29 | 2021 |
Effective numerical methods for huge-scale linear systems with doublesparsity and applications to PageRank AS Anikin, AV Gasnikov, AY Gornov, DI Kamzolov, V Maksimov Yu, ... Proceedings of MIPT 7 (4), 74-94, 2015 | 24* | 2015 |
Representation learning and pairwise ranking for implicit feedback in recommendation systems S Sidana, M Trofimov, O Horodnitskii, C Laclau, Y Maximov, MR Amini arXiv preprint arXiv:1705.00105, 2017 | 21* | 2017 |
Tight risk bounds for multi-class margin classifiers Y Maximov, D Reshetova Pattern Recognition and Image Analysis 26, 673-680, 2016 | 19 | 2016 |
Efficient numerical methods to solve sparse linear equations with application to pagerank A Anikin, A Gasnikov, A Gornov, D Kamzolov, Y Maximov, Y Nesterov Optimization Methods and Software 37 (3), 907-935, 2022 | 17 | 2022 |
Aggressive sampling for multi-class to binary reduction with applications to text classification B Joshi, MR Amini, I Partalas, F Iutzeler, Y Maximov Advances in Neural Information Processing Systems 30, 2017 | 16 | 2017 |
Power grid reliability estimation via adaptive importance sampling A Lukashevich, Y Maximov IEEE Control Systems Letters 6, 1010-1015, 2021 | 15 | 2021 |
Importance sampling approach to chance-constrained dc optimal power flow A Lukashevich, V Gorchakov, P Vorobev, D Deka, Y Maximov IEEE Transactions on Control of Network Systems, 2023 | 12 | 2023 |
Implementation of Boolean functions with a bounded number of zeros by disjunctive normal forms YV Maximov Computational Mathematics and Mathematical Physics 53, 1391-1409, 2013 | 12* | 2013 |
Entropy penalized semidefinite programming M Krechetov, J Marecek, Y Maximov, M Takac arXiv preprint arXiv:1802.04332, 2018 | 11 | 2018 |
Comparative analysis of the complexity of boolean functions with a small number of zeros. Y Maximov Doklady Mathematics 86 (3), 2012 | 11* | 2012 |
Simple disjunctive normal forms of Boolean functions with a restricted number of zeros. Y Maximov Doklady Mathematics 86 (1), 2012 | 10* | 2012 |
Поиск эффективных методов снижения размерности при решении задач многоклассовой классификации путем её сведения к решению бинарных задач МЕ Карасиков, ЮВ Максимов Машинное обучение и анализ данных 1 (9), 1273-1290, 2014 | 9 | 2014 |
Learning model of generator from terminal data N Stulov, DJ Sobajic, Y Maximov, D Deka, M Chertkov Electric Power Systems Research 189, 106742, 2020 | 8 | 2020 |
Gp cc-opf: Gaussian process based optimization tool for chance-constrained optimal power flow M Mitrovic, O Kundacina, A Lukashevich, S Budennyy, P Vorobev, ... Software Impacts 16, 100489, 2023 | 7 | 2023 |