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 ...

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

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 ...

"Blended learning" means any form of learning that mixes methods, such as face-to-face coaching and self-paced, recorded and live, individual and group, etc. In this article, I will explore six key ...

Researchers have demonstrated, for the first time, that transfer learning can significantly enhance material Z-class identification in muon tomography, even in scenarios with limited or completely ...