2 citations · 3 across the 19 of their papers we have counts for
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Efficient Low-Rank Approximation of Quaternion Matrices via Adaptive Cross Approximation
Salman Ahmadi-Asl, Yang Zhang
The adaptive cross approximation (ACA) algorithm is a powerful tool for constructing low-rank matrix approximations using only a small subset of matrix entries. While extensively s…
Adaptive Randomized Pivoting for Tensor Cross Approximation in the T-Product Framework
Ahmadsho Akdodshoev, Valentin Leplat, Salman Ahmadi-Asl
This paper studies extensions of adaptive randomized pivoting (ARP), recently introduced for matrix column subset selection, to tensors in the t-product framework. We propose two c…
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-…
Iterative Methods for Computing the Moore-Penrose Pseudoinverse of Quaternion Matrices, with Applications
Valentin Leplat, Salman Ahmadi-Asl, JunJun Pan +1
We develop quaternion--native iterative methods for computing the Moore--Penrose (MP) pseudoinverse of quaternion matrices and analyze their convergence. Our starting point is a da…
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…
Efficient iterative techniques for solving tensor problems with the T-product
Malihe Nobakht Kooshkghazi, Salman Ahmadi-Asl, Hamidreza Afshin
This paper develops two efficient iterative methods for solving tensor equations under the T-product framework. For T-symmetric positive definite tensor equations of the form $\mat…
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…
Nonnegative Tensor Decomposition Via Collaborative Neurodynamic Optimization
Salman Ahmadi-Asl, Valentin Leplat, Anh-Huy Phan +1
This paper introduces a novel collaborative neurodynamic model for computing nonnegative Canonical Polyadic Decomposition (CPD). The model relies on a system of recurrent neural ne…
Efficient Techniques for Low-Rank Tensor Approximation and Applications in Robust Object Detection
Salman Ahmadi-Asl, Naeim Rezaeian, Cesar F. Caiafa +1
This paper introduces efficient randomized fixed-precision and single-pass algorithms for low-tubal-rank approximation of third-order tensors. The proposed fixed-precision algorith…
Fast randomized Kronecker tensor decomposition: algorithms and error analysis
Salman Ahmadi-Asl, Naeim Rezaeian, Andre L. F. de Almeida +1
This paper proposes fast randomized algorithms for computing the Kronecker Tensor Decomposition (KTD) by replacing the sequence of deterministic SVDs in the TTr1SVD framework with…
Adaptive Cross Tubal Tensor Approximation
Salman Ahmadi-Asl, Anh Huy Phan, Andrzej Cichocki +4
In this paper, we propose a new adaptive cross algorithm for computing a low tubal rank approximation of third-order tensors, with less memory and lower computational complexity th…
Robust Low-Tubal-rank tensor recovery Using Discrete Empirical Interpolation Method with Optimized Slice/Feature Selection
Salman Ahmadi-Asl, Anh-Huy Phan, Cesar F. Caiafa +1
In this paper, we extend the Discrete Empirical Interpolation Method (DEIM) to the third-order tensor case based on the t-product and use it to select important/ significant latera…
Fast randomized algorithms for computing the generalized tensor SVD based on the tubal product
Salman Ahmadi-Asl, Ugochukwu Ugwu
This work deals with developing two fast randomized algorithms for computing the generalized tensor singular value decomposition (GTSVD) based on the tubal product (t-product). The…
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…
A Randomized Algorithm for Tensor Singular Value Decomposition using an Arbitrary Number of Passes
Salman Ahmadi-Asl, Anh-Huy Phan, Andrzej Cichocki
Efficient and fast computation of a tensor singular value decomposition (t-SVD) with a few passes over the underlying data tensor is crucial because of its many potential applicati…
An Efficient Randomized Fixed-Precision Algorithm for Tensor Singular Value Decomposition
Salman Ahmadi-Asl
The existing randomized algorithms need an initial estimation of the tubal rank to compute a tensor singular value decomposition. This paper proposes a new randomized fixedprecisio…
Cross Tensor Approximation for Image and Video Completion
Salman Ahmadi-Asl, Maame Gyamfua Asante-Mensah, Andrzej Cichocki +3
This paper proposes a general framework to use the cross tensor approximation or tensor ColUmn-Row (CUR) approximation for reconstructing incomplete images and videos. The key impo…
Randomized Algorithms for Computation of Tucker decomposition and Higher Order SVD (HOSVD)
Salman Ahmadi-Asl, Stanislav Abukhovich, Maame G. Asante-Mensah +4
Big data analysis has become a crucial part of new emerging technologies such as the internet of things, cyber-physical analysis, deep learning, anomaly detection, etc. Among many…
Tensor Networks for Latent Variable Analysis: Higher Order Canonical Polyadic Decomposition
Anh-Huy Phan, Andrzej Cichocki, Ivan Oseledets +3
The Canonical Polyadic decomposition (CPD) is a convenient and intuitive tool for tensor factorization; however, for higher-order tensors, it often exhibits high computational cost…