Results 31 to 40 of about 143,398 (311)

Relative-Error $CUR$ Matrix Decompositions [PDF]

SIAM Journal on Matrix Analysis and Applications, 2008
Many data analysis applications deal with large matrices and involve approximating the matrix using a small number of ``components.'' Typically, these components are linear combinations of the rows and columns of the matrix, and are thus difficult to interpret in terms of the original features of the input data.
Drineas, Petros, Mahoney, Michael W., Muthukrishnan, S.   +2 more
openaire   +2 more sources

DECOMPOSITION METHOD FOR SOLVING FULLY FUZZY LINEAR SYSTEMS [PDF]

Iranian Journal of Optimization, 2010
In this paper, we investigate the existence of a positive solution of fully fuzzy linear equation systems. This paper mainly to discuss a new decomposition of a nonsingular fuzzy matrix, the symmetric times triangular (ST) decomposition.
M. MOSLEH, M. OTADI, A. KHANMIRZAIE
doaj  

Singular random matrix decompositions: Jacobians [PDF]

Journal of Multivariate Analysis, 2005
For a singular random matrix Y, we find the Jacobians associated with the following decompositions; QR, Polar, Singular Value (SVD), L'U, L'DM and modified QR (QDR). Similarly, we find the Jacobinas of the following decompositions: Spectral, Cholesky's, L'DL and symmetric non-negative definite square root, of the cross-product matrix S = Y'Y.
González Farías, Graciela, Díaz García, José A.   +1 more
openaire   +3 more sources

Improvement of CRF-Based Saliency Detection Algorithm Using Matrix Decomposition Based Features [PDF]

مدیریت مهندسی و رایانش نرم, 2020
One of the most important processing steps in the human vision system is the detection of a scene saliency map. Since saliency map can be applied to algorithms such as segmentation, compression and image retrieval, Researchers have focused on providing ...
Mohammad Shouryabi, Mohammad Javad Fadaeieslam   +1 more
doaj   +1 more source

Singular random matrix decompositions: distributions [PDF]

Journal of Multivariate Analysis, 2005
Assuming that Y has a singular matrix variate elliptically contoured distribution with respect to the Hausdorff measure, the distributions of several matrices associated to QR, modified QR, SV and Polar decompositions of matrix Y are determined, for central and non-central, non-singular and singular cases, as well as their relationship to the Wishart ...
González Farías, Graciela, Díaz García, José A.   +1 more
openaire   +3 more sources

Randomized Matrix Decompositions Using R [PDF]

Journal of Statistical Software, 2019
Matrix decompositions are fundamental tools in the area of applied mathematics, statistical computing, and machine learning. In particular, low-rank matrix decompositions are vital, and widely used for data analysis, dimensionality reduction, and data compression.
Erichson, N. Benjamin, Voronin, Sergey, Brunton, Steven L., Kutz, J. Nathan   +3 more
openaire   +4 more sources

RMPD: Method for Enhancing the Robustness of Recommendations With Attack Environments

IEEE Access, 2021
Personalized item recommendation has become a hot topic research among academic and industry community. But lots of purposeful fraudsters maybe perform different attacks on the recommender system to insert fake ratings, which could reduce the ...
Qi Ding, Peiyu Liu, Zhenfang Zhu, Huajuan Duan, Fuyong Xu   +4 more
doaj   +1 more source

Computing the Polar Decomposition and the Matrix Sign Decomposition in Matrix Groups [PDF]

SIAM Journal on Matrix Analysis and Applications, 2004
The polar decomposition of \(A\) is \(A=UH\), where \(A\) has complex elements, \(U\) is unitary, \(H\) is Hermitian positive semi-definite. The authors identify a family of globally convergent rational iterations that preserve group structure. They show how the structure preservation leads to particularly convenient convergence tests in the case of ...
Higham, Nicholas J., Mackey, D. Steven, Mackey, Niloufer, Tisseur, Françoise   +3 more
openaire   +2 more sources

Decompose Boolean Matrices with Correlation Clustering

Entropy, 2021
One of the tasks of data science is the decomposition of large matrices in order to understand their structures. A special case of this is when we decompose relations, i.e., logical matrices.
László Aszalós
doaj   +1 more source

Peroxidasin enables melanoma immune escape by inhibiting natural killer cell cytotoxicity

Molecular Oncology, EarlyView.
Peroxidasin (PXDN) is secreted by melanoma cells and binds the NK cell receptor NKG2D, thereby suppressing NK cell activation and cytotoxicity. PXDN depletion restores NKG2D signaling and enables effective NK cell–mediated melanoma killing. These findings identify PXDN as a previously unrecognized immune evasion factor and a potential target to improve
Hsu‐Min Sung, David Bickel, Lena C. M. Krause, Daria Ezeriņa, Christian Ickes, Julian Wojtachnia, Christine S. Gibhardt, Magdalena Shumanska, Khadija Wahni, Andrea Paluschkiwitz, Julia Malo Pueyo, Ekaterina Baranova, Wim Vranken, Hedwig Stanisz, Ioana Stejerean‐Todoran, Michael P. Schön, Joris Messens, Ivan Bogeski   +17 more
wiley   +1 more source