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 ...

Multiplication in Python may seem simple at first—just use the * operator—but it actually covers far more than just numbers. You can use * to multiply integers and floats, repeat strings and lists, or ...

Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington 98195, United States ...

Cross-encoder (CE) models evaluate similarity by simultaneously encoding a query-item pair, outperforming the dot-product with embedding-based models at estimating query-item relevance. Current ...

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 PyTorch (GPU) and NumPy (CPU)-based port of Févotte and Dobigeon's robust-NMF algorithm appearing in "Nonlinear hyperspectral unmixing with robust nonnegative matrix factorization." ...