AI-assisted design methods now allow for automated optimization, drastically shortening development cycles while boosting ...

The objective of the study is to identify the most optimal set of hyperparameters for a machine learning (ML) or deep learning(DL) algorithms that improves its performance on a certain task.. This ...

The term dementia is used to describe various debilitating neurological disorders characterized by a progressive loss of ...

Achieving high efficiency, long operational lifetime, and excellent color purity is essential for organic light-emitting ...

AI’s performance advantages are tightly linked to methodological rigor and technological integration. Data preprocessing ...

In the current era of big data, the volume of information continues to grow at an unprecedented rate, giving rise to the crucial need for efficient ...

The strategic advantage of QML continues to expand its presence in industries that deal with complex, high-dimensional data.

A number of hyperparameter optimization techniques for different machine learning models are reviewed in this paper, including grid search, random search, Bayesian optimization, and genetic algorithm.

A suite of machine learning algorithms and SHAP (SHapley Additive exPlanations) interpretation techniques were employed to improve model transparency and predictive accuracy.