Machine learning to predict how fast biodegradable plastics break down in nature

Testing how quickly a biodegradable plastic actually breaks down in the environment can take months, sometimes years, of lab ...
IEEE

Machine-Learning-Based Urban Path Loss Prediction at 900 MHz: Principal Component Analysis, Clustering, Feature Importance and Regression

Abstract: In this work, the possibility of applying machine learning (ML) techniques to analyze and predict radio wave propagation losses in urban environments is explored. Thus, from a measurement ...
IEEE

OFDR Machine Learning Approach with Principal Components Analysis and AutoGluon AutoML Framework for High-Precision Distributed Strain Sensing

Abstract: Optical Frequency Domain Reflectometry (OFDR) has extensive application prospects in structural health monitoring, but faces technical challenges in simultaneously achieving high-precision ...
GitHub

Kernel Local Fisher Discriminant Analysis of Principal Components (KLFDAPC) for large genomic data

R CMD build KLFDAPC R CMD check --as-cran KLFDAPC_0.1.0.tar.gz R CMD INSTALL KLFDAPC_0.1.0.tar.gz Before install or during installation, make sure the below ...
Nature

Quantum enhanced machine learning

Machine learning, and more generally, artificial intelligence, has achieved dramatic success over the past decade. This has been apparent in the tackling of notoriously challenging problems such as ...
International Monetary Fund

Parameter Proliferation in Nowcasting: Issues and Approaches—An Application to Nowcasting China’s Real GDP

This paper evaluates three approaches to address parameter proliferation issue in nowcasting: (i) variable selection using adjusted stepwise autoregressive integrated moving average with exogenous ...
Scientific Research Publishing

Cai, H., Cai, J.-F. and Wei, K. (2019) Accelerated Alternating Projections for Robust Principal Component Analysis. Journal of Machine Learning Research, 20, 685-717.

ABSTRACT: Principal Component Analysis (PCA) is a widely used technique for data analysis and dimensionality reduction, but its sensitivity to feature scale and outliers limits its applicability.
Visual Studio Magazine

Principal Component Analysis from Scratch Using Singular Value Decomposition with C#

Principal Component Analysis from Scratch Using Singular Value Decomposition with C# Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on a classical ML technique ...