Results 81 to 90 of about 138,910 (273)
Reverse annealing for nonnegative/binary matrix factorization.
PLoS ONE, 2021 It was recently shown that quantum annealing can be used as an effective, fast subroutine in certain types of matrix factorization algorithms. The quantum annealing algorithm performed best for quick, approximate answers, but performance rapidly ...
John Golden, Daniel O'Malley
doaj +1 more source
Max–min distance nonnegative matrix factorization
Neural Networks, 2015 Nonnegative Matrix Factorization (NMF) has been a popular representation method for pattern classification problems. It tries to decompose a nonnegative matrix of data samples as the product of a nonnegative basis matrix and a nonnegative coefficient matrix. The columns of the coefficient matrix can be used as new representations of these data samples.
Wang, Jim Jing-Yan, Gao, Xin
openaire +3 more sources
Forecasting House Prices: The Role of Market Interconnectedness
Journal of Forecasting, EarlyView.ABSTRACT While the existing research uncovers interconnections between various housing markets, it largely ignores the question of whether such linkages can improve house price predictions. To address this issue, we proceed in two steps. First, we forecast disaggregated house price growth rates from Australia and China to determine whether ...
Zac Chen +3 more
wiley +1 more source
Discriminative Multiview Nonnegative Matrix Factorization for Classification
IEEE Access, 2019 Multiview nonnegative matrix has shown many promising applications in computer vision and pattern recognition. However, most existing works focus on view consistency and ignore discrimination.
Weihua Ou +4 more
doaj +1 more source
, 2017 This paper explicitly details the relation between $M$-matrices, nonnegative roots of nonnegative matrices, and the embedding problem for finite-state stationary Markov chains.
Van-Brunt, Alexander
core
Intraday Functional PCA Forecasting of Cryptocurrency Returns
Journal of Forecasting, EarlyView.ABSTRACT We study the functional PCA (FPCA) forecasting method in application to functions of intraday returns on Bitcoin. We show that improved interval forecasts of future return functions are obtained when the conditional heteroscedasticity of return functions is taken into account.
Joann Jasiak, Cheng Zhong
wiley +1 more source
Progress of metabolomics‐centric multi‐omics research in medicine
iMetaOmics, EarlyView.The graphical abstract illustrates a holistic roadmap for metabolomics‐centric multi‐omics integration in medical research. The upper panel depicts the technological transition from traditional bulk analysis to high‐resolution single‐cell and spatial methodologies, specifically addressing inherent challenges such as molecular complexity and dynamic ...
Ziyi Wang +6 more
wiley +1 more source
A multilevel approach for nonnegative matrix factorization [PDF]
Nonnegative Matrix Factorization (NMF) is the problem of approximating a nonnegative matrix with the product of two low-rank nonnegative matrices and has been shown to be particularly useful in many applications, e.g., in text mining, image processing ...
GILLIS, Nicolas, GLINEUR, François
core
Bioanalytical TERS and Advanced Data Processing Methods
Journal of Raman Spectroscopy, EarlyView.Tip‐enhanced Raman spectroscopy delivers label‐free, subnanometer vibrational imaging of biological systems. Recent advances in instrumentation, data analysis, and ambient/liquid operation enable surface‐selective mapping of molecular heterogeneity in proteins, nucleic acids, membranes, and viruses, positioning TERS as a powerful platform for nanoscale
Sarika Joshi +6 more
wiley +1 more source
IEEE Access, 2019 Nonnegative matrix factorization (NMF) is a powerful tool for hyperspectral unmixing (HU). This method factorizes a hyperspectral cube into constituent endmembers and their fractional abundances.
Li Sun +3 more
doaj +1 more source