Results 71 to 80 of about 32,711 (308)
Probabilistic Non-Negative Matrix Factorization with Binary Components
Mathematics, 2021 Non-negative matrix factorization is used to find a basic matrix and a weight matrix to approximate the non-negative matrix. It has proven to be a powerful low-rank decomposition technique for non-negative multivariate data.
Xindi Ma +4 more
doaj +1 more source
Business Strategy and the Environment, EarlyView.ABSTRACT This study examines the role of managerial ability in driving environmental performance and overall environmental, social, and governance (ESG) ratings in the context of the European Union sustainability reporting regulations. Using a sample of 7242 firm‐year observations over the period 2015–2023, our results indicate a structural change in ...
Mihaela Ionașcu +2 more
wiley +1 more source
A new Approach for Building Recommender System Using Non-Negative Matrix Factorization Method
پژوهشهای ریاضی, 2021 Nonnegative Matrix Factorization is a new approach to reduce data dimensions. In this method, by applying the nonnegativity of the matrix data, the matrix is decomposed into components that are more interrelated and divide the data into sections where ...
nushin shahrokhi, somayeh arabi narie
doaj
The Canadian Journal of Chemical Engineering, EarlyView.Abstract We develop a delay‐aware estimation and control framework for a non‐isothermal axial dispersion tubular reactor modelled as a coupled parabolic‐hyperbolic PDE system with recycle‐induced state delay. The infinite‐dimensional dynamics are preserved without spatial discretization by representing the delay as a transport PDE and adopting a late ...
Behrad Moadeli, Stevan Dubljevic
wiley +1 more source
Sparsity-Constrained Coupled Nonnegative Matrix–Tensor Factorization for Hyperspectral Unmixing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Hyperspectral unmixing refers to a source separation problem of decomposing a hyperspectral imagery (HSI) to estimate endmembers, and their corresponding abundances.
Heng-Chao Li +3 more
doaj +1 more source
Social Spammer Detection via Convex Nonnegative Matrix Factorization [PDF]
, 2022 Hua Shen +3 more
openalex +1 more source
Heuristics for exact nonnegative matrix factorization [PDF]
Journal of Global Optimization, 2015 32 pages, 2 figures, 16 ...
Arnaud Vandaele +3 more
openaire +5 more sources
Restricted Tweedie stochastic block models
Canadian Journal of Statistics, EarlyView.Abstract The stochastic block model (SBM) is a widely used framework for community detection in networks, where the network structure is typically represented by an adjacency matrix. However, conventional SBMs are not directly applicable to an adjacency matrix that consists of nonnegative zero‐inflated continuous edge weights.
Jie Jian, Mu Zhu, Peijun Sang
wiley +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
Journal of Forecasting, EarlyView.ABSTRACT We study the accuracy of a variety of parametric price duration‐based realized variance estimators constructed via various financial duration models and compare their forecasting performance with the performance of various nonparametric return‐based realized variance estimators.
Björn Schulte‐Tillmann +2 more
wiley +1 more source