LAUSR

Accelerating 4D flow MRI by exploiting low‐rank matrix structure and hadamard sparsity

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1 Published in 2017 at "Magnetic Resonance in Medicine"

DOI: 10.1002/mrm.26508

Abstract: To develop accelerated 4D flow MRI by exploiting low‐rank matrix structure and Hadamard sparsity. read more here.

Keywords: flow mri; matrix structure; exploiting low; rank matrix ... See more keywords

Low-Rank Matrix Recovery with Composite Optimization: Good Conditioning and Rapid Convergence

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0 Published in 2019 at "Foundations of Computational Mathematics"

DOI: 10.1007/s10208-020-09490-9

Abstract: The task of recovering a low-rank matrix from its noisy linear measurements plays a central role in computational science. Smooth formulations of the problem often exhibit an undesirable phenomenon: the condition number, classically defined, scales… read more here.

Keywords: matrix; optimization; rank matrix; low rank ... See more keywords

Improved Gradient Neural Networks for Solving Moore–Penrose Inverse of Full-Rank Matrix

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1 Published in 2019 at "Neural Processing Letters"

DOI: 10.1007/s11063-019-09983-x

Abstract: Being with parallel-computation nature and convenience of hardware implementation, linear gradient neural networks (LGNN) are widely used to solve large-scale online matrix-involved problems. In this paper, two improved GNN (IGNN) models, which are activated by… read more here.

Keywords: moore penrose; full rank; matrix; penrose inverse ... See more keywords

Robust video denoising with sparse and dense noise modelings

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1 Published in 2017 at "Science China Information Sciences"

DOI: 10.1007/s11432-017-9200-6

Abstract: Videos can be contaminated by noise even when captured by high-quality cameras. Because video data has both spatial and temporal redundancies, low rank factorization has been developed. Originally, most denoising methods relied on a single… read more here.

Keywords: video denoising; low rank; noise; rank matrix ... See more keywords

Maximal rank in matrix spaces via graph matchings

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1 Published in 2017 at "Linear Algebra and its Applications"

DOI: 10.1016/j.laa.2017.04.016

Abstract: Let Mn(F)Mn(F) be the space of n×nn×n matrices over a field FF. A matrix A=(A(i,j))i,j=1n∈Mn(F) is weakly symmetric if A(i,j)≠0A(i,j)≠0 iff A(j,i)≠0A(j,i)≠0 holds for all i, j  . A matrix is alternating if it is… read more here.

Keywords: space; matrix spaces; maximal rank; rank matrix ... See more keywords

Sparse and low-rank matrix decomposition based micro-motion target indication in through-the-wall radar

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0 Published in 2017 at "Electronics Letters"

DOI: 10.1049/el.2016.3983

Abstract: Micro-motion indication of human target is widely used in civil and military applications. In through-the-wall (TTW) scenarios, human echo is usually heavily blurred by clutter. This Letter proposes a sparse and low-rank matrix decomposition based… read more here.

Keywords: motion; micro motion; indication; rank matrix ... See more keywords

Speech Enhancement Based on Dictionary Learning and Low-Rank Matrix Decomposition

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0 Published in 2019 at "IEEE Access"

DOI: 10.1109/access.2018.2886991

Abstract: In this paper, a new speech enhancement method is proposed based on dictionary learning and low-rank matrix decomposition with the objective to improve speech quality and intelligibility. In both the learning stage and the enhancement… read more here.

Keywords: low rank; dictionary learning; rank matrix; speech ... See more keywords

A Nonconvex Method to Low-rank Matrix Completion

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2 Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3177592

Abstract: In recent years, the problem of recovering a low-rank matrix from partial entries, known as low-rank matrix completion problem, has attracted much attention in many applications. However, it is a NP-hard problem due to the… read more here.

Keywords: rank matrix; matrix completion; low rank; rank ... See more keywords

Hyperspectral Image Denoising Using Adaptive Weight Graph Total Variation Regularization and Low-Rank Matrix Recovery

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1 Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"

DOI: 10.1109/lgrs.2021.3113078

Abstract: Hyperspectral image (HSI) is often corrupted by various kinds of noises. This letter proposes an innovative HSI denoising approach by leveraging the graph signal processing (GSP) theory and the low-rank (LR) matrix recovery model. With… read more here.

Keywords: rank matrix; hyperspectral image; hsi; low rank ... See more keywords

Diffraction Extraction Using a Low-Rank Matrix Approximation Method

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1 Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"

DOI: 10.1109/lgrs.2022.3187045

Abstract: Subsurface discontinuous features, such as faults, cavities, and pinch-outs, are commonly related to the spatial distribution of hydrocarbon reservoir zones and safe coal mining. Diffractions generated from subsurface discontinuities carry valuable information and thus are… read more here.

Keywords: rank matrix; low rank; method; diffraction extraction ... See more keywords

Low Rank Matrix Factorization Algorithm Based on Multi-Graph Regularization for Detecting Drug-Disease Association.

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1 Published in 2023 at "IEEE/ACM transactions on computational biology and bioinformatics"

DOI: 10.1109/tcbb.2023.3274587

Abstract: Detecting potential associations between drugs and diseases plays an indispensable role in drug development, which has also become a research hotspot in recent years. Compared with traditional methods, some computational approaches have the advantages of… read more here.

Keywords: rank matrix; low rank; regularization; graph regularization ... See more keywords