Optimal Transport for Statistics and Machine Learning
Monday April 4, 2022 | 3.15 pm
Since its introduction more than two centuries ago, optimal transport has flourished into a rich mathematical field allowing us to draw new connections between analysis, geometry, and probability. Recently, thanks to breakneck advances on the computational front, optimal transport has enabled the development of new tools for data analysis, finding applications in a variety of fields ranging from graphics to biology.
Underlying these tools is a new machine learning paradigm where the goal is integrate multiple data sources. This talk will illustrate this new paradigm in light of several applications and discuss some of the statistical challenges associated with it.