Maxim Rakhuba

Junior researcher at Skoltech

Research interests

All publications, sorted by year

1. Valentin Khrulkov, Maxim Rakhuba, and Ivan Oseledets. Vico-Greengard-Ferrando quadratures in the tensor solver for integral equations. arXiv preprint 1704.01669, 2017. URL: http://arxiv.org/abs/1704.01669. [ bib ]
2. Ivan Oseledets, Maxim Rakhuba, and André Uschmajew. Alternating least squares as moving subspace correction. arXiv preprint 1709.07286, 2017. URL: http://arxiv.org/abs/1709.07286. [ bib ]
3. Maxim Rakhuba and Ivan Oseledets. Jacobi-Davidson method on low-rank matrix manifolds. arXiv preprint 1605.03795, 2017. URL: http://arxiv.org/abs/1703.0906. [ bib ]
4. A. V. Chertkov, I. V Oseledets, and M. V. Rakhuba. Robust discretization in quantized tensor train format for elliptic problems in two dimensions. arXiv preprint 1612.01166, 2016. URL: http://arxiv.org/abs/1612.01166. [ bib ]
5. Vladimir Kazeev, Ivan Oseledets, Maxim Rakhuba, and Christoph Schwab. QTT-finite-element approximation for multiscale problems I: model problems in one dimension. Adv. Comp. Math., 2016. URL: http://www.sam.math.ethz.ch/reports/2016/06, doi:10.1007/s10444-016-9491-y. [ bib ]
6. Ivan V. Oseledets, Maxim V. Rakhuba, and Andrei V. Chertkov. Black-box solver for multiscale modelling using the QTT format. In Proc. ECCOMAS. Crete Island, Greece, 2016. URL: https://www.eccomas2016.org/proceedings/pdf/10906.pdf. [ bib ]
7. M. V. Rakhuba and I. V. Oseledets. Grid-based electronic structure calculations: the tensor decomposition approach. J. Comp. Phys., 2016. URL: http://arxiv.org/abs/1508.07632, doi:10.1016/j.jcp.2016.02.023. [ bib ]
8. Maxim Rakhuba and Ivan Oseledets. Calculating vibrational spectra of molecules using tensor train decomposition. J. Chem. Phys., 145:124101, 2016. doi:10.1063/1.4962420. [ bib ]
9. M. V. Rakhuba and I. V. Oseledets. Fast multidimensional convolution in low-rank tensor formats via cross approximation. SIAM J. Sci. Comput., 37(2):A565–A582, 2015. doi:10.1137/140958529. [ bib ]
10. Vadim Lebedev, Yaroslav Ganin, Maxim Rakhuba, Ivan Oseledets, and Victor Lempitsky. Speeding up convolutional neural networks using fine-tuned CP-decomposition. arXiv preprint 1412.6553, 2014. URL: http://arxiv.org/abs/1412.6553. [ bib ]