Statistical Relational Learning
Lise Getoor · 2017
Machine learning and database approaches to structured probabilistic models share many commonalities, yet exhibit certain important differences. Machine learning methods focus on learning probabilistic models from (certain) data and efficient learning and inference, whereas probabilistic database approaches focus on storing and efficiently querying uncertain data. Nonetheless, the structured probabilistic models that both use are often (almost) identical. In this tutorial, I will overview the field of statistical relational learning (SRL) [1] and survey common approaches. I'll make connections to work in probabilistic databases [2], and highlight commonalities and differences among them. I'll close by describing some of our recent work on probabilistic soft logic [3].