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 from Peking University conducts a systematic review of studies on integrating machine learning into statistical methods in disease prediction models. Researchers from Peking University have ...

"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 ...

Education is undergoing a revolutionary transformation in an era marked by rapid technological advancements. The technology of education, once a mere facilitator, now shapes how we learn, teach and ...

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 ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...

Methods of K-12 teaching encompass diverse strategies and techniques utilized by educators to engage students across different subjects and grade levels. What are the 5 methods of teaching? From ...

The IAEA has launched an innovative, interactive e‑learning course on approaches and methods to help countries perform prospective radiological environmental impact assessment (REIA). Nuclear ...