Mathematical Foundations of Graph-Based Bayesian Semi-Supervised Learning
- Series
- Applied and Computational Mathematics Seminar
- Time
- Monday, April 10, 2023 - 14:00 for 1 hour (actually 50 minutes)
- Location
- Skiles 005 and https://gatech.zoom.us/j/98355006347
- Speaker
- Prof. Daniel Sanz-Alonso – U Chicago
Please Note: Speaker will present in person
Semi-supervised learning refers to the problem of recovering an input-output map using many unlabeled examples and a few labeled ones. In this talk I will survey several mathematical questions arising from the Bayesian formulation of graph-based semi-supervised learning. These questions include the modeling of prior distributions for functions on graphs, the derivation of continuum limits for the posterior, the design of scalable posterior sampling algorithms, and the contraction of the posterior in the large data limit.