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

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 ...

Collaborative filtering generates recommendations by exploiting user-item similarities based on rating data, which often contains numerous unrated items. To predict scores for unrated items, matrix ...

Streaming has undoubtedly changed how we watch movies. While nothing can replace the theatrical experience, the pros of streaming ultimately outweigh the cons. That being said, the prices are getting ...

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, ...

Asynchronous Many-Task Systems and Applications: Second International Workshop, WAMTA 2024, Knoxville, TN, USA, February 14–16, 2024 The ubiquitous in-node heterogeneity of HPC and cloud computing ...

An analysis of leaf litter breakdown in climatically diverse habitats shows that decomposition by larger invertebrates dominates in hot, dry regions and warmer seasons. Researchers have shown that ...

Codes and data coming with article "A Survey and an Extensive Evaluation of Popular Audio Declipping Methods", and others closely related ...