Matrix factorization techniques have become pivotal in data mining, enabling the extraction of latent structures from large-scale data matrices. These methods decompose complex datasets into ...
COMPANY: CODTECH IT SOLUTIONS NAME: ABHIJEET KUMAR INTERN ID: CTO4DG2125 DOMAIN: MACHINE LEARNING DURATION: 4 WEEKS MENTOR: NEELA SANTOSH DESCRIPTIONS : In this project, My aim to build a ...
Abstract: Matrix factorization (MF) is a major technique for collaborative filtering of recommender systems. However, in the traditional MF model, it is difficult to tune the regularization parameter, ...
Abstract: Multi-view clustering (MVC) has gained attention for its ability to efficiently handle complex high-dimensional data. Many existing MVC methods rely on a technique known as Nonnegative ...
X: shared genes by cells matrix of ST data. Y: shared genes by cells matrix of scRNA-seq data. Z: unique genes by cells matrix of scRNA-seq data. L1: cells by cells matrix. A precomputed normalized ...
Matrix decomposition is an area of linear algebra which is focused on expressing a matrix as a product of matrices with prescribed properties. (Photo credit: Merino et al., 2024) Imagine discovering ...
1 School of Public Health and Management, Chongqing Three Gorges Medical College, Chongqing, China 2 Department of Environment and Food Hygiene, Chongqing Wanzhou District Center for Disease Control ...
Results that may be inaccessible to you are currently showing.
Hide inaccessible results