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.
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.