CS 152-03 Learning from Limited Labeled Data

This course will study machine learning methods that can learn from available labeled datasets of limited size to perform a desired task well by leveraging either some other abundant source of related data or a pre-trained model. Topics will include self-supervised learning, semi-supervised learning, transfer learning, and more. The goal of this course is to bring students to the forefront of knowledge in this area. Students will engage in discussions of recent literature and complete a semester-long team research project designing, implementing, evaluating, and communicating new contributions to this research area.