Results 231 to 240 of about 303,055 (260)

Learning to rank with a Weight Matrix

The 2010 14th International Conference on Computer Supported Cooperative Work in Design, 2010
Learning to rank, a task applying machine learning techniques to rank the expected information of the users, such as movie items users might be interested in. It is useful for collaborative filtering, which is regarded as a hot subfield of computer supported collaborative work(CSCW).
Zewu Peng, Yong Tang 0001, Luxian Lin, Yan Pan 0002   +3 more
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Integer matrix rank certification

Proceedings of the 2009 international symposium on Symbolic and algebraic computation, 2009
Let M = [A B/C D] be a 2n x 2n integer matrix with the principal block A square and nonsingular. An algorithm is presented to determine if the Schur complement D--CA--1B is equal to the zero matrix in O~(nω log ||M||) bit operations. Here, ω is the exponent of matrix multiplication and ||M|| denotes the largest entry in absolute value. The algorithm is
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Matrix Inversion by the Annihilation of Rank

Journal of the Society for Industrial and Applied Mathematics, 1959
can be readily verified, and provides a method of finding the inverse of a matrix which differs from a matrix of known inverse by a matrix of raiik unity. Equation (1) was originally derived by Sherman and Morrison [1], used by Bartlett [2], and generalized by Woodbury [3], as reported by Householder [4]. Now, since an arbitrary matrix can obviously be
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Maximum Matching and the Rank of a Matrix

SIAM Journal on Applied Mathematics, 1975
The rank of a matrix A is related to the cardinality of a maximum matching in a graph G formed from A by considering whether the matrix entries of A are nonzero, but ignoring their magnitudes otherwise. We consider real matrices which can be written as the sum of a skew matrix and a diagonal matrix.
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On the Rank of a Matrix

Resonance, 2021
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Robust rank-one matrix completion with rank estimation

Pattern Recognition, 2023
Feiping Nie, Ziheng Li
exaly  

Color Image Recovery Using Low-Rank Quaternion Matrix Completion Algorithm

IEEE Transactions on Image Processing, 2022
Jifei Miao, Kit Ian Kou
exaly  

Analysis of the Properties of Matrix Rank and the Relationship between Matrix Rank and Matrix Operations

Dynamic Systems and Applications, 2020
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Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization

SIAM Review, 2010
Benjamin Recht, Pablo A Parrilo, Maryam Fazel   +2 more
exaly  

Nonnegative low rank matrix approximation for nonnegative matrices

Applied Mathematics Letters, 2020
Michael Ng, Guang-Jing Song
exaly