Abstract: As an effective feature extraction and dimensionality reduction technique, nonnegative matrix factorization (NMF) has been widely applied in fault detection in recent years. The requirement ...

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: In this paper, an Optimal Predictive Modeling of Nonlinear Transformations “OPMNT” method has been developed while using Orthogonal Nonnegative Matrix Factorization “ONMF” with the ...

Is your feature request related to a problem? Please describe. We wish to use cuML to accelerate our experiment on Identifying gene expression programs of cell-type identity and cellular activity.

Using advanced microscopes that capture brain cell anatomy and activity, a portion of a mouse's brain was mapped and rendered into a 3D atlas that creates new possibilities for neuroscience. When you ...

The Toyota Matrix was discontinued just over 10 years ago and it's already been pretty much forgotten. While it was dropped in the U.S. ahead of 2014 (and a year later for Canada), the Matrix had ...

Hello! I would like to know how to debug this error: "[ERROR PSM-0010] LU factorization of the G Matrix failed. SparseLU solver message: THE MATRIX IS STRUCTURALLY SINGULAR ... ZERO COLUMN AT" I have ...

The increased availability of multi-view data (data on the same samples from multiple sources) has led to strong interest in models based on low-rank matrix factorizations. These models represent each ...

An international criminal communications network, known as the Matrix, containing more than 2 million encrypted messages in 33 languages and spanning 40 servers, has been broken apart by a ...