6 papers
Scalable Amortized Variational Inference for Non-Poisson Buy-'Til-You-Die Models
Sulagna Ghosh, Aaron Schein
Despite the wide variety of existing Buy-`Til-You-Die (BTYD) models, nearly all rely upon the convenient assumption of transactions following a Poisson process. As modern customer…
Bayesian Poisson-Randomized Gamma Tensor Factorization with Application to International Trade Flows
Jie Jian, Aaron Schein
We study sparse semi-continuous tensor data with excess zeros, heavy right tails, and slice-specific dispersion. Such features arise naturally in monetary-valued multi-way data, su…
The Triply-Randomized Negative Binomial Beta for Robust Regression and Conjugate Models of Bounded Support Data
Jimmy Lederman, Aaron Schein
The beta distribution is the default choice of likelihood in many regression problems with a -bounded support response despite its sensitivity to outliers, inability to acco…
Discrete Causal Representations from Heterogeneous Domains: A Bayesian Approach with Social Survey Applications
Ankur Garg, Michael Stettler, Aaron Schein +1
Causal representation learning aims to infer the high-level latent causal concepts that give rise to observed low-level measurements. This is particularly relevant for heterogeneou…
Doubly Non-Central Beta Matrix Factorization for Stable Dimensionality Reduction of Bounded Support Matrix Data
Anjali N. Albert, Patrick Flaherty, Aaron Schein
We consider the problem of developing interpretable and computationally efficient matrix decomposition methods for matrices whose entries have bounded support. Such matrices are fo…
Addressing Discretization-Induced Bias in Demographic Prediction
Evan Dong, Aaron Schein, Yixin Wang +1
Racial and other demographic imputation is necessary for many applications, especially in auditing disparities and outreach targeting in political campaigns. The canonical approach…