8 citations · 10 across the 4 of their papers we have counts for
6 papers
A Recommender System Based on a Double Feature Allocation Model
Qiaohui Lin, Peter Mueller
A collaborative filtering recommender system predicts user preferences by discovering common features among users and items. We implement such inference using a Bayesian double fea…
Separate Exchangeability as Modeling Principle in Bayesian Nonparametrics
Giovanni Rebaudo, Qiaohui Lin, Peter Mueller
We argue for the use of separate exchangeability as a modeling principle in Bayesian nonparametric (BNP) inference. Separate exchangeability is \emph{de facto} widely applied in th…
A Unified Decision Framework for Phase I Dose-Finding Designs
Yunshan Duan, Shijie Yuan, Yuan Ji +1
The purpose of a phase I dose-finding clinical trial is to investigate the toxicity profiles of various doses for a new drug and identify the maximum tolerated dose. Over the past…
Bayesian Scalable Precision Factor Analysis for Massive Sparse Gaussian Graphical Models
Noirrit Kiran Chandra, Peter Mueller, Abhra Sarkar
We propose a novel approach to estimating the precision matrix of multivariate Gaussian data that relies on decomposing them into a low-rank and a diagonal component. Such decompos…
The Dependent Dirichlet Process and Related Models
Fernand A. Quintana, Peter Mueller, Alejandro Jara +1
Standard regression approaches assume that some finite number of the response distribution characteristics, such as location and scale, change as a (parametric or nonparametric) fu…
Clustering and Prediction with Variable Dimension Covariates
Garritt L. Page, Fernando A. Quintana, Peter Müller
In many applied fields incomplete covariate vectors are commonly encountered. It is well known that this can be problematic when making inference on model parameters, but its impac…