Real-world data typically exhibits long-tailed class distribution and contains label noise. Previous long-tail learning ...

Active learning represents a transformative paradigm in machine learning, aimed at reducing the annotation burden by selectively querying the most informative data points. This approach leverages ...

Scientists have developed a geometric deep learning method that can create a coherent picture of neuronal population activity during cognitive and motor tasks across experimental subjects and ...

Learning happened through doing, not consuming. It felt distinctly human. And it stuck. Last week, I returned to Ivey as a ...

Deep learning techniques can enhance diagnosis of Meniere disease (MD) and severity grading, according to a study published ...

Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...

Active learning puts students at the center of the learning process by encouraging them to engage, reflect, and apply what they’re learning in meaningful ways. Rather than passively receiving ...

A research team from the Aerospace Information Research Institute of the Chinese Academy of Sciences (AIRCAS) has developed a ...

Virginia Clinton-Lisell receives funding from the U.S. Department of Education and Hewlett Foundation. Students do better when lessons are tailored to individual learning styles – but not so much that ...