Friday, April 25th
12:00pm - 1:00pm, Zoom/ARB 627
Meeting ID: 957 7525 9475
Passcode: 834911
Minghe Wang
MS in Biostatistics Student
Columbia University
Understanding and Addressing Covariate Shift in Transfer Learning Part 2
Abstract:
Building on the foundational concepts of covariate shift problem introduced in the first lecture, this session will explore advanced covariate shift adjustment methods that estimate importance weights as a whole rather than separately. We will cover Kernel Mean Matching, Kullback-Leibler Divergence Minimization, and Least-squares-based techniques. These methods offer improved stability and efficiency in high-dimensional settings, making them especially relevant for modern healthcare datasets. The lecture will include hands-on examples to illustrate how these approaches can be implemented and evaluated in practice. By the end of this session, participants will be more familiar with covariant shift problem and the application of importance weighting methods.
Speaker Bio:
Minghe Wang is a first-year Master's student in Biostatistics. He received his Bachelor's degree in Applied Mathematics, with a minor in Computer Science, from New York University. He will be leading the lectures and labs for this series of tutorials, under the mentorship of Drs. Tian Gu and Ying Wei.
About TRAIL4Health & the Brown Bag Learning Series
TRAIL4Health is a Translational AI Laboratory committed to advancing public health through innovative applications of artificial intelligence and data science. At TRAIL4Health, we host a variety of events to foster learning, collaboration, and the exchange of ideas at the intersection of AI, public health, and medicine.
The TRAIL Brown Bag Learning Series is a weekly informal gathering held on Fridays at noon in Room 627 of the Allen Rosenfield Building. These sessions are an opportunity for faculty, students, and researchers to come together and learn something new—whether it be a dataset, software, new article, or simply to exchange ideas. This informal setting provides a platform for sharing knowledge, stimulating discussions, and fostering collaboration in a relaxed environment.