IEEE

A Comprehensive Survey on Dimension Reduction for Medical Big Data Using Optimization Algorithms

Abstract: This paper surveys dimension reduction techniques in medical big data using optimization algorithms to address challenges like computational inefficiency, overfitting, and inter-pretability ...

The Structural Paradox of Jekyll and Hyde

My Nieman Labs piece (“Google Will Look Beyond Volume Journalism”) sparked a vital debate. Much of the feedback focused on ...
IEEE

Effects of Dimension Reduction Methods on Boosting Algorithms for Better Prediction Accuracies on Classifications of Stress EEGs

Abstract: This research aims to investigate the effects of various dimension reduction methods, namely Principal Component Analysis (PCA), Independent Component Analysis (ICA) and Linear Discriminant ...
Frontiers

Dimension reduction and entropy-based hyperspectral image visualization using hue, saturation, and brightness

Hyperspectral imaging (HSI) captures rich spectral data across hundreds of contiguous bands for diverse applications. Dimension reduction (DR) techniques are commonly used to map the first three ...