216 citations · 454 across the 55 of their papers we have counts for
4 papers · 1 filter
Automated Dependence Plots
David I. Inouye, Liu Leqi, Joon Sik Kim +2
In practical applications of machine learning, it is necessary to look beyond standard metrics such as test accuracy in order to validate various qualitative properties of a model.…
Learning Sample-Specific Models with Low-Rank Personalized Regression
Benjamin Lengerich, Bryon Aragam, Eric P. Xing
Modern applications of machine learning (ML) deal with increasingly heterogeneous datasets comprised of data collected from overlapping latent subpopulations. As a result, traditio…
On perfectness in Gaussian graphical models
Arash A. Amini, Bryon Aragam, Qing Zhou
Knowing when a graphical model is perfect to a distribution is essential in order to relate separation in the graph to conditional independence in the distribution, and this is par…
Learning Sparse Nonparametric DAGs
Xun Zheng, Chen Dan, Bryon Aragam +2
We develop a framework for learning sparse nonparametric directed acyclic graphs (DAGs) from data. Our approach is based on a recent algebraic characterization of DAGs that led to…