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 ...

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

South Korean researchers have developed a guided-learning framework that accurately predicts PV power without requiring irradiance sensors during operation, using routine meteorological data instead.

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 ...

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

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

Rules-based automation (RBA) and learning are two training mechanisms in robotics. While there are many others, these are two ...

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 ...

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 ...