High-fat diet accelerates triple-negative breast cancer growth in engineered tumors

A multidisciplinary team of researchers at Princeton University conducted a study to find out what patients diagnosed with ...
techxplore

Tiny silicon structures compute with heat, achieving 99% accurate matrix multiplication

MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat instead of electricity. These tiny structures could someday enable more ...
The New York Times

How a G.O.P. Senator Quietly Became a Best-Selling Author

Senator John Kennedy, a garrulous rank-and-file Republican from Louisiana, has struck a nerve with a new book that provides an insider account of Congress and its dysfunction. By Catie Edmondson ...
Frontiers

Interleaving cortex-analog mixing improves deep non-negative matrix factorization networks

1 Institute for Theoretical Physics, University of Bremen, Bremen, Germany 2 Institute of Electrodynamics and Microelectronics (ITEM.ids), University of Bremen, Bremen, Germany Considering biological ...
Scientific Research Publishing

Shiga, M. and Muto, S. (2019) Non-Negative Matrix Factorization and Its Extensions for Spectral Image Data Analysis. e-Journal of Surface Science and Nanotechnology, 17, 148-154.

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 ...
Scientific Research Publishing

Qi, Q., Zhao, Y., Li, M. and Simon, R. (2009) Non-Negative Matrix Factorization of Gene Expression Profiles: A Plug-In for Brb-Arraytools. Bioinformatics, 25, 545-547.

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 ...
TheServerSide

False positives vs false negatives in machine learning

Community driven content discussing all aspects of software development from DevOps to design patterns. The key difference between a false positive and a false negative is that a false positive ...
IEEE

Non-Negative Matrix Factorization and Latent Semantic Analysis for Hybrid Feature Selection: A Proposed Machine Learning System for the Detection of Malicious Executable Files

Abstract: During a typical cyber-attack lifecycle, several key phases are involved, including footprinting and reconnaissance, scanning, exploitation, and covering tracks. The successful delivery of a ...
GitHub

Proposal: Accelerate Non-Negative Matrix Factorization (NMF) needed for Dimensionality Reduction

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.
Frontiers

Geochemical-process extraction and interpretation using matrix factorization: a framework for verifying effectiveness through forward modeling and inversion analysis

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, ...