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 ...

Kernel methods represent a cornerstone in modern machine learning, enabling algorithms to efficiently derive non-linear patterns by implicitly mapping data into high‐dimensional feature spaces. At the ...

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 ...

Current continual learning methods can utilize labeled data to alleviate catastrophic forgetting effectively. However, ...

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft Your email has been sent A new “periodic table for machine learning” is reshaping how researchers explore AI, ...

Adult learning in the United States continues to evolve as colleges, universities, and professional programs adapt to the ...

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 ...

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 ...

Stroke is the second leading cause of death globally. Ischemic stroke, strongly linked to atherosclerotic plaques, requires accurate plaque and vessel wall segmentation and quantification for ...

A scientist in Sweden has developed a new hybrid local features-based method using thermographs to identify faulty solar panels. A researcher from Sweden’s Jönköping University has proposed a machine ...