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Minimally Supervised Learning
(e.g., Active Learning, Transfer Learning)
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Courses at Columbia

Undergraduate:

  • STAT 4541 (Spring 26). Honors Statistical Machine Learning. (Syllabus)

  • STAT 4241 (Spring 24-25, 25-26). Statistical Machine Learning. (Syllabus)

  • STAT 1201 (Fall 19-20). Calculus-based Introduction to Statistics. (Syllabus)

Graduate (Masters):

  • STAT 5242 (Fall 20-21, 21-22, 23-24). Advanced Machine Learning (Syllabus)
    (co-taught with J. P. Cunningham, Kamiar R. Rad, Parijat Dude)

Graduate (PhD):

  • STAT 6203 (Fall 25-26). Theoretical Statistics III (Vignettes in Statistical Learning Theory). (Syllabus)

  • STAT 8201 (Spring 22-23). Topics in Theoretical Statistics: Nonparametric Theory in ML. (Syllabus)

  • STAT 6103 (Spring 20-21). Applied Statistics III (Nonparametric Theory in ML). (Syllabus)

  • STAT 8201 (Spring 18-19). Topics in Theoretical Statistics: Kernel Machines. (Syllabus)

Former Courses at Princeton

Undergraduate:

  • ORF 245/ENG 245 (Spring 14-15, 15-16, 16-17, 17-18). Fundamentals of Statistics. (Syllabus)

Graduate (PhD):

  • ORF 524 (Fall 15-16, 16-17, 17-18, 18-19). Statistical Theory and Methods. (Syllabus)