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 ...

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

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 ...

Database optimization has long relied on traditional methods that struggle with the complexities of modern data environments. These methods often fail to efficiently handle large-scale data, complex ...

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...

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 ...