| Randomized Block Cubic Newton Method N Doikov, P Richtárik ICML 2018 (International Conference on Machine Learning), 2018 | 16 | 2018 |
| Minimizing Uniformly Convex Functions by Cubic Regularization of Newton Method N Doikov, Y Nesterov arXiv preprint arXiv:1905.02671, 2019 | 13 | 2019 |
| Local convergence of tensor methods N Doikov, Y Nesterov CORE Discussion Papers; 2019/21, 2019 | 7 | 2019 |
| Contracting Proximal Methods for Smooth Convex Optimization N Doikov, Y Nesterov CORE Discussion Papers; 2019/27, 2019 | 5 | 2019 |
| Stochastic Subspace Cubic Newton Method F Hanzely, N Doikov, P Richtárik, Y Nesterov ICML 2020 (International Conference on Machine Learning), 2020 | 3 | 2020 |
| Многокритериальные и многомодальные вероятностные тематические модели коллекций текстовых документов КВ Воронцов, АА Потапенко, АИ Фрей, МА Апишев, НВ Дойков, ... 10-я Междунар. конф. ИОИ, 198, 2014 | 2 | 2014 |
| Convex optimization based on global lower second-order models N Doikov, Y Nesterov Advances in Neural Information Processing Systems 33, 2020 | 1 | 2020 |
| Inexact Tensor Methods with Dynamic Accuracies N Doikov, Y Nesterov ICML 2020 (International Conference on Machine Learning), 2020 | 1 | 2020 |
| Affine-invariant contracting-point methods for Convex Optimization N Doikov, Y Nesterov arXiv preprint arXiv:2009.08894, 2020 | | 2020 |
Yurii NesterovProfessor of Université catholique de Louvain (UCL), CORE(IMMAQ) and INMA(ICTEAM, EPL)Verified email at uclouvain.be
