Nature

Active Learning for Multi-Label Classification

Active learning for multi-label classification addresses the challenge of labelling data in situations where each instance may belong to several overlapping categories. This paradigm aims to enhance ...
Nature

Active Learning Algorithms and Methods

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 ...
EurekAlert!

Active label distribution learning via kernel maximum mean discrepancy

Label Distribution Learning (LDL) is a new learning paradigm to deal with label ambiguity and many researches have achieved the prominent performances. Compared with traditional supervised learning ...
TechCrunch

Active learning is the future of generative AI: Here’s how to leverage it

During the past six months, we have witnessed some incredible developments in AI. The release of Stable Diffusion forever changed the artworld, and ChatGPT-3 shook up the internet with its ability to ...
Drexel University

Active Learning and the Science of Learning

College students are habituated to a classroom norm sociologists call civil attention: creating the appearance of paying attention (sitting still, looking awake, scribbling or typing) while ...
Baylor College of Medicine

Active Learning Workshops

Active learning is not a new concept. Though coined by Bonwell and Eisen (1991), aspects of active learning can be found in studies by Piaget, Vygotsky, and Dewey*. Active Learning is a broad set of ...
Drexel University

Active and Collaborative Learning Strategies

Active and Collaborative Learning Strategies The classic: think-pair-share Think-pair-share (TPS) is the black dress of active learning: a highly flexible tool that can take as little or as much time ...