Randomized linear algebra for model reduction. Part I: Galerkin methods and error estimation. - Oleg Balabanov; Anthony Nouy (Adv. Comput. Math., 2019)

Randomized linear algebra for model order reduction. (Algèbre linéaire randomisée pour la réduction de l'ordre des modèles). - Oleg Balabanov (2019)

Randomized linear algebra for model reduction - part II: minimal residual methods and dictionary-based approximation. - Oleg Balabanov; Anthony Nouy (Adv. Comput. Math., 2021)

Preconditioners for model order reduction by interpolation and random sketching of operators. - Oleg Balabanov; Anthony Nouy (CoRR, 2021)

Randomized Cholesky QR factorizations. - Oleg Balabanov (CoRR, 2022)

Block subsampled randomized Hadamard transform for low-rank approximation on distributed architectures. - Oleg Balabanov; Matthias Beaupère; Laura Grigori; Victor Lederer (CoRR, 2022)

Randomized Gram-Schmidt Process with Application to GMRES. - Oleg Balabanov; Laura Grigori (SIAM J. Sci. Comput., 2022)

Block Subsampled Randomized Hadamard Transform for Nyström Approximation on Distributed Architectures. - Oleg Balabanov; Matthias Beaupère; Laura Grigori; Victor Lederer (ICML, 2023)

Randomized Orthogonal Projection Methods for Krylov Subspace Solvers. - Edouard Timsit; Laura Grigori; Oleg Balabanov (CoRR, 2023)

CholeskyQR with Randomization and Pivoting for Tall Matrices (CQRRPT). - Maksim Melnichenko; Oleg Balabanov; Riley Murray; James Demmel; Michael W. Mahoney; Piotr Luszczek (SIAM J. Matrix Anal. Appl., 2025)

Randomized Block Gram-Schmidt Process for the Solution of Linear Systems and Eigenvalue Problems. - Oleg Balabanov; Laura Grigori (SIAM J. Sci. Comput., 2025)

LIFT the Veil for the Truth: Principal Weights Emerge after Rank Reduction for Reasoning-Focused Supervised Fine-Tuning. - Zihang Liu; Tianyu Pang; Oleg Balabanov; Chaoqun Yang; Tianjin Huang; Lu Yin 006; Yaoqing Yang; Shiwei Liu 003 (CoRR, 2025)