Special Topics in Machine Learning and Data Visualization

(3 Credit Hours) · Undergraduate

This seminar course is for graduate students interested in machine learning (ML) and data visualization (VIS). ML+VIS has emerged as the most vibrant direction in visualization research. ML+VIS encompasses two primary branches: ML4VIS (i.e., designing ML solutions for solving VIS problems) and VIS4ML (i.e., applying VIS techniques for explainable ML). The topics include representation learning, data generation, data reconstruction, visualization generation for ML4VIS, interpretation of the inner workings of neural networks, network model debugging, improvement, comparison, and selection for VIS4ML. This course is also suitable for students interested in research areas beyond VIS, such as medical imaging, computer vision, and human-computer interaction. Students will read and present relevant scientific papers and complete a related class project.