| Variance reduction for Markov chains with application to MCMC D Belomestny, L Iosipoi, E Moulines, A Naumov, S Samsonov Statistics and Computing 30, 973-997, 2020 | 24 | 2020 |
| Variance reduction via empirical variance minimization: convergence and complexity D Belomestny, L Iosipoi, N Zhivotovskiy arXiv preprint arXiv:1712.04667, 2017 | 16 | 2017 |
| Variance reduction for dependent sequences with applications to stochastic gradient MCMC D Belomestny, L Iosipoi, E Moulines, A Naumov, S Samsonov SIAM/ASA Journal on Uncertainty Quantification 9 (2), 507-535, 2021 | 10 | 2021 |
| Empirical variance minimization with applications in variance reduction and optimal control D Belomestny, L Iosipoi, Q Paris, N Zhivotovskiy Bernoulli 28 (2), 1382-1407, 2022 | 8* | 2022 |
| Variance reduction in monte carlo estimators via empirical variance minimization DV Belomestny, LS Iosipoi, NK Zhivotovskiy Doklady Mathematics 98, 494-497, 2018 | 7 | 2018 |
| SketchBoost: Fast Gradient Boosted Decision Tree for Multioutput Problems L Iosipoi, A Vakhrushev Advances in Neural Information Processing Systems 35, 25422-25435, 2022 | 3 | 2022 |
| Fourier transform MCMC, heavy-tailed distributions, and geometric ergodicity D Belomestny, L Iosipoi Mathematics and Computers in Simulation 181, 351-363, 2021 | 2 | 2021 |
| On density estimation via fourier series DV Belomestny, L Iosipoi Upravlenie Bol'shimi Sistemami 82, 28-43, 2019 | | 2019 |
| SketchBoost: Fast Gradient Boosted Decision Tree for Multioutput Problems, Supplementary Material L Iosipoi, A Vakhrushev | | |
Prof. Dr. Denis BelomestnyDuisburg-Essen UniversityVerified email at uni-due.de
