Oleg Balabanov

According to our database, Oleg Balabanov authored at least 12 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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, Yaoqing Yang, Shiwei Liu

CoRR, June, 2025

Randomized Block Gram-Schmidt Process for the Solution of Linear Systems and Eigenvalue Problems.

Oleg Balabanov, Laura Grigori

SIAM J. Sci. Comput., 2025

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

2023

Randomized Orthogonal Projection Methods for Krylov Subspace Solvers.

Edouard Timsit, Laura Grigori, Oleg Balabanov

CoRR, 2023

Block Subsampled Randomized Hadamard Transform for Nyström Approximation on Distributed Architectures.

Oleg Balabanov, Matthias Beaupère, Laura Grigori, Victor Lederer

Proceedings of the International Conference on Machine Learning, 2023

2022

Randomized Gram-Schmidt Process with Application to GMRES.

Oleg Balabanov, Laura Grigori

SIAM J. Sci. Comput., 2022

Block subsampled randomized Hadamard transform for low-rank approximation on distributed architectures.

Oleg Balabanov, Matthias Beaupère, Laura Grigori, Victor Lederer

CoRR, 2022

Randomized Cholesky QR factorizations.

Oleg Balabanov

CoRR, 2022

2021

Preconditioners for model order reduction by interpolation and random sketching of operators.

Oleg Balabanov, Anthony Nouy

CoRR, 2021

Randomized linear algebra for model reduction - part II: minimal residual methods and dictionary-based approximation.

Oleg Balabanov, Anthony Nouy

Adv. Comput. Math., 2021

2019

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

Oleg Balabanov

PhD thesis, 2019

Randomized linear algebra for model reduction. Part I: Galerkin methods and error estimation.

Oleg Balabanov, Anthony Nouy

Adv. Comput. Math., 2019