Talk page

Title:
Fusion with Optimal Transport

Speaker:
Justin Solomon

Abstract:
Many problems in learning and statistics involve fusing potentially conflicting signals into a single coherent observation about a system or environment. Optimal transport provides a valuable language for posing and solving such fusion problems in a mathematically-justified and efficient framework. In this talk, I will summarize efforts in our group on developing efficient algorithms for model fusion drawing from state-of-the-art algorithms for computational transport.

Link:
https://www.msri.org/workshops/928/schedules/28413

Workshop:
MSRI- [Moved Online] Hot Topics: Optimal transport and applications to machine learning and statistics