Results 51 to 60 of about 137,800 (236)

Some new bounds on the spectral radius of nonnegative matrices

open access: yesAIMS Mathematics, 2020
In this paper, we determine some new bounds for the spectral radius of a nonnegative matrix with respect to a new defined quantity, which can be considered as an average of average 2-row sums.
Maria Adam   +2 more
doaj   +1 more source

Adaptive Kernel Graph Nonnegative Matrix Factorization

open access: yesInformation, 2023
Nonnegative matrix factorization (NMF) is an efficient method for feature learning in the field of machine learning and data mining. To investigate the nonlinear characteristics of datasets, kernel-method-based NMF (KNMF) and its graph-regularized ...
Rui-Yu Li, Yu Guo, Bin Zhang
doaj   +1 more source

Sufficient conditions to be exceptional

open access: yesSpecial Matrices, 2016
A copositive matrix A is said to be exceptional if it is not the sum of a positive semidefinite matrix and a nonnegative matrix. We show that with certain assumptions on A−1, especially on the diagonal entries, we can guarantee that a copositive matrix A
Johnson Charles R., Reams Robert B.
doaj   +1 more source

On the complexity of nonnegative-matrix scaling

open access: yesLinear Algebra and its Applications, 1996
AbstractAn n × n nonnegative matrix A is said to be (doubly stochastic) scalable if there exist two positive diagonal matrices X and Y such that XAY is doubly stochastic. We derive an upper bound on the norms of the scaling factors X and Y and give a polynomial-time complexity bound on the problem of computing the scaling factors to a prescribed ...
Bahman Kalantari, Leonid Khachiyan
openaire   +2 more sources

Non-negative Matrix Factorization for Dimensionality Reduction [PDF]

open access: yesITM Web of Conferences, 2022
—What matrix factorization methods do is reduce the dimensionality of the data without losing any important information. In this work, we present the Non-negative Matrix Factorization (NMF) method, focusing on its advantages concerning other methods of ...
Olaya Jbari, Otman Chakkor
doaj   +1 more source

Benefits of Open Quantum Systems for Quantum Machine Learning

open access: yesAdvanced Quantum Technologies, EarlyView., 2023
Quantum machine learning (QML), poised to transform data processing, faces challenges from environmental noise and dissipation. While traditional efforts seek to combat these hindrances, this perspective proposes harnessing them for potential advantages. Surprisingly, under certain conditions, noise and dissipation can benefit QML.
María Laura Olivera‐Atencio   +2 more
wiley   +1 more source

Multi-Component Nonnegative Matrix Factorization [PDF]

open access: yesProceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017
Real data are usually complex and contain various components. For example, face images have expressions and genders. Each component mainly reflects one aspect of data and provides information others do not have. Therefore, exploring the semantic information of multiple components as well as the diversity among them is of great benefit to understand ...
Wang, Jing   +8 more
openaire   +3 more sources

Nonnegative Matrix Factorization Requires Irrationality [PDF]

open access: yesSIAM Journal on Applied Algebra and Geometry, 2017
Nonnegative matrix factorization (NMF) is the problem of decomposing a given nonnegative $n \times m$ matrix $M$ into a product of a nonnegative $n \times d$ matrix $W$ and a nonnegative $d \times m$ matrix $H$. A longstanding open question, posed by Cohen and Rothblum in 1993, is whether a rational matrix $M$ always has an NMF of minimal inner ...
Chistikov, D   +4 more
openaire   +4 more sources

Exponents of nonnegative matrix pairs

open access: yesLinear Algebra and its Applications, 2003
AbstractThe notions of primitivity and exponent of a square nonnegative matrix A are classical: A is primitive provided there is a nonnegative integer k such that Ak is entrywise positive and in the case A is primitive the exponent of A is the smallest such k.
Saib Suwilo, Bryan L. Shader
openaire   +2 more sources

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