Results 21 to 30 of about 1,507,141 (306)
Incremental Reduced Least Squares Twin Support Vector Regression
Jisuanji kexue yu tansuo, 2021 In the incremental least squares twin support vector regression, to solve the problem that the constituted kernel matrix cannot approximate the original kernel matrix well, this paper proposes an incremental reduced least squares twin support vector ...
CAO Jie, GU Binjie, XIONG Weili, PAN Feng
doaj +1 more source
Geospatial Least Squares Support Vector Regression Fused with Spatial Weight Matrix
ISPRS International Journal of Geo-Information, 2021 Due to the increasingly complex objects and massive information involved in spatial statistics analysis, least squares support vector regression (LS-SVR) with a good stability and high calculation speed is widely applied in regression problems of ...
Haiqi Wang +6 more
doaj +1 more source
Nuclear matrix support of DNA replication [PDF]
Journal of Cellular Biochemistry, 2005 AbstractIn higher eukaryotic cells, DNA is tandemly arranged into 104 replicons that are replicated once per cell cycle during the S phase. To achieve this, DNA is organized into loops attached to the nuclear matrix. Each loop represents one individual replicon with the origin of replication localized within the loop and the ends of the replicon ...
Boyka, Anachkova, V, Djeliova, G, Russev
openaire +2 more sources
The praxis of matrix support: Interdisciplinary work in primary health care
Salud Colectiva, 2021 Family health support centers have been implemented in Brazil in order to expand interdisciplinary work in primary care by hiring specialized professionals.
Tatiana de Vasconcellos Anéas
doaj +1 more source
Permanent education and matrix support in primary health care: family health routine [PDF]
Revista Brasileira de Enfermagem, 2020 Objective: To analyze the understanding of the professionals working on the Family Health Support by about permanent education and matrix support in the daily routine of primary health care.
Danilo Carvalho Rodrigues +6 more
doaj +3 more sources
Decision Support System dalam Menentukan Mahasiswa Bermasalah Menggunakan Metode Topsis
Jurnal Ilmiah Informatika, 2020 At present many old semester students are starting to be undisciplined in attending lectures, this is due to the increasing burden of their assignments causing the enthusiasm of students to relax.
Adinda Dhea Pramitha +3 more
doaj +1 more source
Structured Support Exploration for Multilayer Sparse Matrix Factorization [PDF]
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021 Matrix factorization with sparsity constraints plays an important role in many machine learning and signal processing problems such as dictionary learning, data visualization, dimension reduction. Among the most popular tools for sparse matrix factorization are proximal algorithms, a family of algorithms based on proximal operators.
Le, Quoc-Tung, Gribonval, Rémi
openaire +2 more sources
Nurses' contributions to matrix support in mental health in primary health care
Revista de Enfermagem da Universidade Federal de Santa Maria, 2021 Objective: to identify the nurses' contributions in the context of matrix support in mental health in primary health care. Method: a qualitative research study, based on the Fourth Generation Assessment, carried out with workers from matrix support ...
Guilherme Emanuel Weiss Pinheiro +1 more
doaj +1 more source
A nonlinear kernel support matrix machine for matrix learning [PDF]
International Journal of Machine Learning and Cybernetics, 2018 In many problems of supervised tensor learning (STL), real world data such as face images or MRI scans are naturally represented as matrices, which are also called as second order tensors. Most existing classifiers based on tensor representation, such as support tensor machine (STM) need to solve iteratively which occupy much time and may suffer from ...
openaire +2 more sources
Covariance matrix forecasting using support vector regression [PDF]
Applied Intelligence, 2021 AbstractSupport vector regression is a promising method for time-series prediction, as it has good generalisability and an overall stable behaviour. Recent studies have shown that it can describe the dynamic characteristics of financial processes and make more accurate forecasts than other machine learning techniques.
Piotr Fiszeder, Witold Orzeszko
openaire +1 more source