Nature

Low-Rank Approximation and Dimensionality Reduction Techniques

Low-rank approximation and dimensionality reduction techniques form the backbone of modern computational methods by enabling the efficient representation of large and high‐dimensional datasets. These ...
VentureBeat

Understanding dimensionality reduction in machine learning models

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Machine learning algorithms have gained fame for being able to ferret out ...
ascopubs.org

Interrogating machine learning classifiers and dimensionality reduction techniques for radiomic prediction of glioma tumor grade.

Meningioma: Association of mean and "hot spot" MIB1 with grade. This is an ASCO Meeting Abstract from the 2018 ASCO Annual Meeting I. This abstract does not include a full text component.
Visual Studio Magazine

Data Dimensionality Reduction Using a Neural Autoencoder with C#

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on creating an approximation of a dataset that has fewer columns. Imagine that you have a dataset that has many ...