Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations

Abstract

Paper presentation.

Date
Dec 10, 2020 7:30 AM — 7:40 AM
Location
Online
Zhe Zeng
Zhe Zeng
Ph.D. student in AI

My research interests lie in the intersection of machine learning (probabilistic modeling, statistical relational learning, neuro-symbolic AI) and formal methods. My research goal is to enable machine learning models to incorporate diverse forms of constraints into probabilistic inference and learning in a principled way.