New seminar class in Fall 2018 and Spring 2019: Topics in Deep Learning (STAT-991), surveying advanced topics in deep learning research based on student presentations. See here for the syllabus and for the lecture notes.
This seminar will be taken by doctoral candidates after the completion of most of their coursework. Topics vary from year to year and are chosen from advance probability, statistical inference, robust methods, and decision theory with principal emphasis on applications.
P-value weighting techniques for multiple hypothesis testing. These can improve power in multiple testing, if there is prior information about the individual effect sizes. Includes the iGWAS method for Genome-Wide Association Studies.