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Neural networks, ISSN 0893-6080, 2018, Volume 98, pp. 34 - 41
Journal Article
Information sciences, ISSN 0020-0255, 2016, Volume 326, pp. 243 - 257
In this paper, we study the problem of recovering a tensor with missing data. We propose a new model combining the total variation regularization and low-rank matrix factorization... 
Total variation | Tensor completion | Low-rank matrix factorization | Block coordinate descent | COMPUTER SCIENCE, INFORMATION SYSTEMS | ALGORITHM | Analysis | Algorithms | Tensors | Mathematical analysis | Blocking | Mathematical models | Regularization | Factorization | Optimization
Journal Article
IEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, 07/2018, Volume 40, Issue 7, pp. 1726 - 1740
Journal Article
Pattern recognition, ISSN 0031-3203, 2008, Volume 41, Issue 4, pp. 1350 - 1362
Journal Article
Neurocomputing (Amsterdam), ISSN 0925-2312, 2017, Volume 241, pp. 115 - 127
•We proposed a robust unsupervised method to remove redundant and irrelevant features.•Both the cluster centers and the sparse representation are... 
Unsupervised feature selection | Matrix factorization | Manifold regularization | l2, 1-norm | norm | LOW-RANK REPRESENTATION | INFORMATION | l(2,1)-norm | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Information science | Algorithms | Computer science | Usage | Data mining | Machine learning
Journal Article
Inverse Problems and Imaging, ISSN 1930-8337, 2015, Volume 9, Issue 2, pp. 601 - 624
.... We propose a new model to recover a low-rank tensor by simultaneously performing low-rank matrix factorizations to the all-mode matricizations of the underlying tensor... 
Higher-order tensor | Non-convex optimization | Alternating least squares | Low-rank tensor completion | Low-rank matrix completion | alternating least squares | COORDINATE DESCENT METHOD | low-rank matrix completion | non-convex optimization | MATHEMATICS, APPLIED | low-rank tensor completion | ALGORITHM | CONVERGENCE | PHYSICS, MATHEMATICAL | LEAST-SQUARES
Journal Article
Neurocomputing, ISSN 0925-2312, 11/2017, Volume 266, pp. 91 - 100
Nonnegative matrix factorization (NMF) is a very effective technique for image representation, which has been widely applied in computer vision and pattern recognition... 
Image representation | Label information | Nonnegative matrix factorization | Semi-supervised learning | CONSTRAINED CONCEPT FACTORIZATION | SPARSE GRAPH | PARTS | MODEL | LOW-RANK | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Machine vision
Journal Article
ETRI Journal, ISSN 1225-6463, 02/2017, Volume 39, Issue 1, pp. 21 - 29
Journal Article
SIAM journal on scientific computing, ISSN 1095-7197, 2019, Volume 41, Issue 3, pp. A1652 - A1680
.... Their discretization leads to a dense kernel matrix that is block or hierarchically low-rank. This paper proposes a new way to build a low-rank factorization of those low-rank blocks at a nearly optimal cost of O(nr... 
DECOMPOSITIONS | MATHEMATICS, APPLIED | interpolation | kernel | skeletonization | low-rank | rank-revealing QR | INTEGRAL-EQUATIONS | ALGORITHMS | OPERATORS | Chebyshev | CROSS APPROXIMATION
Journal Article
IEEE transactions on signal processing, ISSN 1941-0476, 2019, Volume 67, Issue 2, pp. 490 - 503
Journal Article
IEEE Transactions on Signal Processing, ISSN 1053-587X, 11/2018, Volume 66, Issue 21, pp. 5520 - 5533
Journal Article
IEEE transactions on geoscience and remote sensing, ISSN 1558-0644, 2016, Volume 54, Issue 1, pp. 178 - 188
...)-regularized low-rank matrix factorization (LRTV). In general, HSIs are not only assumed to lie in a low-rank subspace from the spectral perspective but also assumed to be piecewise smooth in the spatial dimension... 
Gaussian noise | total variation (TV) | rank constraint | Hyperspectral image (HSI) | Image restoration | Sparse matrices | low-rank matrix factorization | restoration | Hyperspectral imaging | QUALITY | IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY | ALGORITHMS | ENGINEERING, ELECTRICAL & ELECTRONIC | GEOCHEMISTRY & GEOPHYSICS | REMOTE SENSING | SPARSE REPRESENTATION | NOISE-REDUCTION | Noise | Television | Images | Norms | Gaussian | Spectra | Regularization | Factorization
Journal Article
IEEE transactions on information theory, ISSN 1557-9654, 2018, Volume 64, Issue 3, pp. 1666 - 1698
Journal Article
IEEE transactions on signal processing, ISSN 1941-0476, 2018, Volume 66, Issue 22, pp. 5917 - 5926
We study convex optimization problems that feature low-rank matrix solutions. In such scenarios, non-convex methods offer significant advantages over convex... 
Gradient methods | Non-convex optimization | non-Euclidean gradient descent | Signal processing algorithms | Machine learning | Matrix decomposition | low-rank approximation | Standards | Convergence | MINIMIZATION | OPTIMIZATION | SEMIDEFINITE | ENGINEERING, ELECTRICAL & ELECTRONIC | Convexity | Smoothness | Optimization | Dependence
Journal Article