As a fundamental technology of artificial intelligence, existing machine learning (ML) methods often rely on extensive human intervention and manually presetting, like manually collecting, selecting, ...

Legacy systems and “one-size-fits-all” learning models are shifting alongside military leadership culture. As more digital ...

Affective computing, a field focused on understanding and emulating human emotions, has seen significant advancements thanks to deep learning. However, researchers at the Technical University of ...

The evolving landscape of higher education has prompted extensive examination into the diverse learning styles and preferences exhibited by students. Recognising that learners process and retain ...

Unsupervised machine learning explores data to find new patterns without set goals. It fuels advancements in tech fields like autonomous driving and content recommendations. Investors can use ...

E-learning and blended learning methodologies, either on its own or in a hybrid/mixed model, have become more frequently used for delivering capacity development activities. The COVID-19 Pandemic has ...

On the methodology front, our paper contributes to the climate toolbox by identifying country-specific structural breaks in emissions for top 20 emitters based on a user-friendly machine-learning tool ...

Machine learning can predict many things, but can it predict who will develop schizophrenia years before the average diagnosis time?

North Korean authorities are pushing research-based learning in schools, but teachers say poor conditions and political ...