EECE 7373 — Machine Learning with Small Data

4 semester hoursGraduateLecture

Addresses machine learning in small-data regimes, focusing on methods that enable learning with limited supervision and scarce labeled data. Topics include formal learning theory, transfer learning, domain adaptation, weak supervision, zero- and few-shot learning, multitask learning, and meta-learning. Further explores data augmentation through data-driven and physics-based simulation. Introduces modern generative approaches for data-efficient representation learning.

Prerequisites

• EECE 5644 (min C-)

Links

Official catalog (EECE course descriptions) · All EECE courses · Plan it at numap.app