collaborators

13 papers

math.NA2026

Adaptive Randomized Pivoting for Tensor Singular Value Decomposition Model

Ahmadsho Akdodshoev, Valentin Leplat, Salman Ahmadi-Asl

This paper studies how adaptive randomized pivoting (ARP), recently introduced for matrix column subset selection, can be extended to tensors in the t-product framework. We propose…

math.NA2026

Pass-efficient Randomized Algorithms for Low-rank Approximation of Quaternion Matrices

Salman Ahmadi-Asl, Malihe Nobakht Kooshkghazi, Valentin Leplat

Randomized algorithms for low-rank approximation of quaternion matrices have gained increasing attention in recent years. However, existing methods overlook pass efficiency, the ab…

math.NA2026

Randomized block Krylov method for approximation of truncated tensor SVD

Malihe Nobakht Kooshkghazi, Salman Ahmadi-Asl, Andre L. F. de Almeida

This paper is devoted to studying the application of the block Krylov subspace method for approximation of the truncated tensor SVD (T-SVD). The theoretical results of the proposed…

math.NA2026

A New Tensor Network: Tubal Tensor Train and Its Applications

Salman Ahmadi-Asl, Valentin Leplat, Anh-Huy Phan +1

We introduce the tubal tensor train (TTT) decomposition, a tensor-network model that combines the t-product algebra of the tensor singular value decomposition (T-SVD) with the low-…

math.NA2026

A note on generalized tensor CUR approximation for tensor pairs and tensor triplets based on the tubal product

Salman Ahmadi-Asl, Naeim Rezaeian, Keivan Ramazani

In this note, we briefly present a generalized tensor CUR (GTCUR) approximation for tensor pairs (X,Y) and tensor triplets (X,Y,Z) based on the tubal product (t-product). We use th…

cs.LG2025

SAGE: Streaming Agreement-Driven Gradient Sketches for Representative Subset Selection

Ashish Jha, Salman Ahmadi-Asl

Training modern neural networks on large datasets is computationally and energy intensive. We present SAGE, a streaming data-subset selection method that maintains a compact Freque…