Scalable and Sample-Efficient Active Learning in Graph-Based Semi-Supervised Classification


Presented work at University of Minnesota’s (UMN) IMA Data Science Seminar, per the invitation of Dr. Jeffrey Calder. Presented my recent work on active learning with application to Hyperspectral Imagery (HSI) and Synthetic Aperture Radar (SAR) data, including specific focus and discussion about exploration and exploitation in active learning.

See my poster here.