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

Tight and Efficient Upper Bound on Spectral Norm of Convolutional Layers. - Ekaterina Grishina; Mikhail Gorbunov; Maxim Rakhuba (CoRR, 2024)

ProcrustesGPT: Compressing LLMs with Structured Matrices and Orthogonal Transformations. - Ekaterina Grishina; Mikhail Gorbunov; Maxim Rakhuba (ACL (Findings), 2025)

Knowledge Graph Completion with Mixed Geometry Tensor Factorization. - Viacheslav Yusupov; Maxim Rakhuba; Evgeny Frolov (AISTATS, 2025)

Accelerating Newton-Schulz Iteration for Orthogonalization via Chebyshev-type Polynomials. - Ekaterina Grishina; Matvey Smirnov; Maxim Rakhuba (CoRR, 2025)

On the Upper Bounds for the Matrix Spectral Norm. - Alexey Naumov; Maxim Rakhuba; Denis Ryapolov; Sergey Samsonov (CoRR, 2025)

COALA: Numerically Stable and Efficient Framework for Context-Aware Low-Rank Approximation. - Uliana Parkina; Maxim Rakhuba (CoRR, 2025)

Pay Attention to Attention Distribution: A New Local Lipschitz Bound for Transformers. - Nikolay Yudin; Alexander Gaponov; Sergei Kudriashov; Maxim Rakhuba (CoRR, 2025)

RiemannLoRA: A Unified Riemannian Framework for Ambiguity-Free LoRA Optimization. - Vladimir Bogachev; Vladimir Aletov; Alexander Molozhavenko; Denis Bobkov; Vera Soboleva; Aibek Alanov; Maxim Rakhuba (CoRR, 2025)

Matrix-Free Two-to-Infinity and One-to-Two Norms Estimation. - Askar Tsyganov; Evgeny Frolov; Sergey Samsonov; Maxim Rakhuba (CoRR, 2025)

Leveraging Geometric Insights in Hyperbolic Triplet Loss for Improved Recommendations. - Viacheslav Yusupov; Maxim Rakhuba; Evgeny Frolov (CoRR, 2025)