Abstract: Matrix factorization is a fundamental characterization model in machine learning and is usually solved using mathematical decomposition reconstruction loss. However, matrix factorization is ...

Tensor Extraction of Latent Features (T-ELF). Within T-ELF's arsenal are non-negative matrix and tensor factorization solutions, equipped with automatic model determination (also known as the ...

Hello! I'm a dreamer focusing on high-load distributed systems and low-level engineering. I mainly code in Rust and Python ...

ABSTRACT: The offline course “Home Plant Health Care,” which is available to the senior population, serves as the study object for this paper. Learn how to use artificial intelligence technologies to ...

Matrix factorization techniques, such as principal component analysis (PCA) and independent component analysis (ICA), are widely used to extract geological processes from geochemical data. However, ...

Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China State Key Laboratory of Loess and Quaternary Geology, CAS ...

Python is convenient and flexible, yet notably slower than other languages for raw computational speed. The Python ecosystem has compensated with tools that make crunching numbers at scale in Python ...