Rakhuba, Maxim

10 publications

NeurIPS 2025 COALA: Numerically Stable and Efficient Framework for Context-Aware Low-Rank Approximation Uliana Parkina, Maxim Rakhuba

AISTATS 2025 Knowledge Graph Completion with Mixed Geometry Tensor Factorization Viacheslav Yusupov, Maxim Rakhuba, Evgeny Frolov

COLT 2024 Dimension-Free Structured Covariance Estimation Nikita Puchkin, Maxim Rakhuba

NeurIPS 2024 Group and Shuffle: Efficient Structured Orthogonal Parametrization Mikhail Gorbunov, Nikolay Yudin, Vera Soboleva, Aibek Alanov, Alexey Naumov, Maxim Rakhuba

ECCV 2024 Tight and Efficient Upper Bound on Spectral Norm of Convolutional Layers Ekaterina Grishina, Mikhail Gorbunov, Maxim Rakhuba

AISTATS 2024 Training a Tucker Model with Shared Factors: A Riemannian Optimization Approach Ivan Peshekhonov, Aleksey Arzhantsev, Maxim Rakhuba

NeurIPS 2022 Towards Practical Control of Singular Values of Convolutional Layers Alexandra Senderovich, Ekaterina Bulatova, Anton Obukhov, Maxim Rakhuba

AISTATS 2021 Spectral Tensor Train Parameterization of Deep Learning Layers Anton Obukhov, Maxim Rakhuba, Alexander Liniger, Zhiwu Huang, Stamatios Georgoulis, Dengxin Dai, Luc Van Gool

ICCV 2021 Cherry-Picking Gradients: Learning Low-Rank Embeddings of Visual Data via Differentiable Cross-Approximation Mikhail Usvyatsov, Anastasia Makarova, Rafael Ballester-Ripoll, Maxim Rakhuba, Andreas Krause, Konrad Schindler

ICML 2020 T-Basis: A Compact Representation for Neural Networks Anton Obukhov, Maxim Rakhuba, Stamatios Georgoulis, Menelaos Kanakis, Dengxin Dai, Luc Van Gool