The new reinforcement learning system lets large language models challenge and improve themselves using real-world data ...
ABSTRACT: In this paper, we explore the application of predictive modeling within the field of Learning Analytics (LA) to forecast student academic success in higher education. Utilizing the Open ...
When kids tinker in the classroom, they get to build many useful skills from computing to collaboration to creativity and more. Krithik Ranjan, PhD student and member of the ACME Lab, studies low-cost ...
Self-learning AI enhances behavioral analytics for detecting advanced threats and insider risks, but demands careful attention to bias, transparency, and ethical use. Self-learning AI improves threat ...
High-precision GNSS applications, such as real-time displacement monitoring and vehicle navigation, rely heavily on resolving carrier-phase ambiguities. However, traditional methods like the R-ratio ...
Abstract: The application of deep learning has significantly accelerated magnetic resonance imaging (MRI). However, these methods encounter substantial challenges when fully sampled datasets are ...
Researchers have developed a new machine learning algorithm that excels at interpreting optical spectra, potentially enabling faster and more precise medical diagnoses and sample analysis. Researchers ...
Ambuj Tewari receives funding from NSF and NIH. Understanding intelligence and creating intelligent machines are grand scientific challenges of our times. The ability to learn from experience is a ...
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