Timezone: »
We propose a Bayesian regression method that accounts for multi-way interactions of arbitrary orders among the predictor variables. Our model makes use of a factorization mechanism for representing the regression coefficients of interactions among the predictors, while the interaction selection is guided by a prior distribution on random hypergraphs, a construction which generalizes the Finite Feature Model. We present a posterior inference algorithm based on Gibbs sampling, and establish posterior consistency of our regression model. Our method is evaluated with extensive experiments on simulated data and demonstrated to be able to identify meaningful interactions in applications in genetics and retail demand forecasting.
Author Information
Mikhail Yurochkin (IBM Research AI)
I am working as a Research Staff Member at the IBM Research AI in Cambridge. Before, I have completed PhD in Statistics at the University of Michigan, advised by Prof. Long Nguyen. I received my bachelor degree in applied mathematics and physics from Moscow Institute of Physics and Technology.
Long Nguyen (University of Michigan)
nikolaos Vasiloglou (LogicBlox)
More from the Same Authors
-
2020 Poster: Continuous Regularized Wasserstein Barycenters »
Lingxiao Li · Aude Genevay · Mikhail Yurochkin · Justin M Solomon -
2020 Demonstration: IBM Federated Learning Community Edition: An Interactive Demonstration »
Laura Wynter · Chaitanya Kumar · Pengqian Yu · Mikhail Yurochkin · Amogh Tarcar -
2019 Poster: Alleviating Label Switching with Optimal Transport »
Pierre Monteiller · Sebastian Claici · Edward Chien · Farzaneh Mirzazadeh · Justin M Solomon · Mikhail Yurochkin -
2019 Poster: Hierarchical Optimal Transport for Document Representation »
Mikhail Yurochkin · Sebastian Claici · Edward Chien · Farzaneh Mirzazadeh · Justin M Solomon -
2019 Poster: Scalable inference of topic evolution via models for latent geometric structures »
Mikhail Yurochkin · Zhiwei Fan · Aritra Guha · Paraschos Koutris · XuanLong Nguyen -
2019 Poster: Statistical Model Aggregation via Parameter Matching »
Mikhail Yurochkin · Mayank Agarwal · Soumya Ghosh · Kristjan Greenewald · Nghia Hoang -
2017 Poster: Conic Scan-and-Cover algorithms for nonparametric topic modeling »
Mikhail Yurochkin · Aritra Guha · XuanLong Nguyen -
2016 Poster: Geometric Dirichlet Means Algorithm for topic inference »
Mikhail Yurochkin · XuanLong Nguyen -
2014 Poster: Parallel Feature Selection Inspired by Group Testing »
Yingbo Zhou · Utkarsh Porwal · Ce Zhang · Hung Q Ngo · XuanLong Nguyen · Christopher RĂ© · Venu Govindaraju -
2013 Poster: Bayesian inference as iterated random functions with applications to sequential inference in graphical models »
Arash Amini · XuanLong Nguyen -
2013 Spotlight: Bayesian inference as iterated random functions with applications to sequential inference in graphical models »
Arash Amini · XuanLong Nguyen -
2007 Spotlight: Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization »
XuanLong Nguyen · Martin J Wainwright · Michael Jordan -
2007 Poster: Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization »
XuanLong Nguyen · Martin J Wainwright · Michael Jordan -
2006 Poster: Distributed PCA and Network Anomaly Detection »
Ling Huang · XuanLong Nguyen · Minos Garofalakis · Michael Jordan · Anthony D Joseph · Nina Taft