Abstract: Machine learning (ML) has been widely adopted in modern software, but the manual configuration of ML (e.g., hyper-parameter configuration) poses a significant challenge to software ...

Abstract: The five papers in this special section address different aspects of automated machine learning (AutoML) from fundamental algorithms to real-world applications. Developing high-performance ...

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Automated Machine Learning (AutoML) aims to streamline the end-to-end process of ML models, yet current approaches remain constrained by rigid rule-based frameworks and structured input requirements ...

Automation is the king of modern technologies. Or at least one of them. Most business tasks are subject to automation in one way or another. This is especially true for routine and repetitive ...

AutoML for Embedded, developed by Analog Devices (ADI) and Antmicro, is an open-source plugin for Visual Studio Code that works alongside ADI’s CodeFusion Studio plugin. Built on the Kenning framework ...

Artificial intelligence (AI) is rapidly moving to the edge with demand for intelligent edge devices exploding, but many developers still struggle to fit powerful models onto tiny microcontrollers.

This study focuses on the innovative application of Automated Machine Learning (AutoML) technology in cardiovascular medicine to construct an explainable Coronary Artery Disease (CAD) prediction model ...