Maxim V. Rakhuba

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 16

Top Topics

Singular Values

Optimization Methods

Top Venues

Numer. Linear Algebra Appl.

J. Comput. Phys.

Publications

Ivan Peshekhonov, Aleksey Arzhantsev, Maxim V. Rakhuba
Training a Tucker Model With Shared Factors: a Riemannian Optimization Approach. AISTATS (2024)
Nikita Puchkin, Maxim V. Rakhuba
Dimension-free Structured Covariance Estimation. COLT (2024)
Lev I. Vysotsky, Maxim V. Rakhuba
Tensor rank bounds and explicit QTT representations for the inverses of circulant matrices. Numer. Linear Algebra Appl. 30 (3) (2023)
Ivan V. Oseledets, Maxim V. Rakhuba, André Uschmajew
Local convergence of alternating low-rank optimization methods with overrelaxation. Numer. Linear Algebra Appl. 30 (3) (2023)
Vladimir A. Kazeev, Ivan V. Oseledets, Maxim V. Rakhuba, Christoph Schwab
Quantized Tensor FEM for Multiscale Problems: Diffusion Problems in Two and Three Dimensions. Multiscale Model. Simul. 20 (3) (2022)
Alexandra Senderovich, Ekaterina Bulatova, Anton Obukhov, Maxim V. Rakhuba
Towards Practical Control of Singular Values of Convolutional Layers. NeurIPS (2022)
Ivan V. Oseledets, Maxim V. Rakhuba, André Uschmajew
Local convergence of alternating low-rank optimization methods with overrelaxation. CoRR (2021)
Anton Obukhov, Maxim V. Rakhuba, Alexander Liniger, Zhiwu Huang, Stamatios Georgoulis, Dengxin Dai, Luc Van Gool
Spectral Tensor Train Parameterization of Deep Learning Layers. AISTATS (2021)
Alexander Novikov, Maxim V. Rakhuba, Ivan V. Oseledets
Automatic differentiation for Riemannian optimization on low-rank matrix and tensor-train manifolds. CoRR (2021)
Anton Obukhov, Maxim V. Rakhuba, Alexander Liniger, Zhiwu Huang, Stamatios Georgoulis, Dengxin Dai, Luc Van Gool
Spectral Tensor Train Parameterization of Deep Learning Layers. CoRR (2021)
Anton Obukhov, Maxim V. Rakhuba, Stamatios Georgoulis, Menelaos Kanakis, Dengxin Dai, Luc Van Gool
T-Basis: a Compact Representation for Neural Networks. CoRR (2020)
Anton Obukhov, Maxim V. Rakhuba, Stamatios Georgoulis, Menelaos Kanakis, Dengxin Dai, Luc Van Gool
T-Basis: a Compact Representation for Neural Networks. ICML (2020)
Carlo Marcati, Maxim V. Rakhuba, Johan E. M. Ulander
Low rank tensor approximation of singularly perturbed partial differential equations in one dimension. CoRR (2020)
Carlo Marcati, Maxim V. Rakhuba, Christoph Schwab
. CoRR (2019)
Maxim V. Rakhuba, Alexander Novikov, Ivan V. Oseledets
Low-rank Riemannian eigensolver for high-dimensional Hamiltonians. J. Comput. Phys. 396 (2019)
Ivan V. Oseledets, Maxim V. Rakhuba, André Uschmajew
Alternating Least Squares as Moving Subspace Correction. SIAM J. Numer. Anal. 56 (6) (2018)