A Common Model, Separated by Two Disciplines


We're starting off the new year with a talk about both R and Stan.

Thank you to New York Presbyterian for hosting.

About the Talk:
Factorization machines are a powerful, flexible, and interpretable tool for modeling interactions between variables. However, there are a dearth of implementations of these models which allow for principled uncertainty estimates, especially in R. This talk will discuss implementing Bayesian Factorization Machines in R and Stan, first introducing basic models, and then, extending these models using techniques from modern hierarchical Bayesian modeling.

About Adam:
Adam Lauretig is the Senior Data Scientist at JUST Capital, where he works on Bayesian discrete-choice models, ranking methodology, and analyzing survey data. Previously, he completed his Ph.D. in political methodology at The Ohio State University, where he developed Bayesian Word Embeddings to study decision-making American Foreign Policy, and worked on a project with the World Bank, examining the effects of democratization on discrimination in the Indonesian Civil Service.

Pizza (https://bit.ly/pizzapoll) begins at 6:30, the talk starts at 7, then after we head to the local bar.