IEEE

Multispace Dimensionality Reduction Based on Extreme Learning Machine-Assisted Autoencoder for High-Dimensional Expensive Optimization

Abstract: Faced with high-dimensional expensive optimization problems (HEOPs), existing high-dimensional expensive optimization algorithms (HEOAs) struggle to locate promising areas quickly due to a ...
Beebom

What is the Difference Between Deep Learning and Machine Learning

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...
Frontiers

Estimating rice yield-related traits using machine learning models integrating hyperspectral and texture features

Rapidly estimating multiple trait indicators simultaneously, nondestructively, and with high precision is an important means of accurate diagnosis in modern phenomics. Increasing the accuracy of ...
Scientific Research Publishing

Van Der Maaten, L., Postma, E. and Van den Herik, J. (2009) Dimensionality Reduction: A Comparative Review. Journal of Machine Learning Research, 10, 66-71.

ABSTRACT: Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language ...
IEEE

Research on Feature Extraction and Dimensionality Reduction of Machine Learning Neural Networks in Big Data Processing

Abstract: With the innovative application of machine learning neural networks, the problem of feature extraction and dimensionality reduction in big data processing has received extensive attention, ...