167 citations · 472 across the 12 of their papers we have counts for
12 papers
Fitting a deeply-nested hierarchical model to a large book review dataset using a moment-based estimator
Ningshan Zhang, Kyle Schmaus, Patrick O. Perry
We consider a particular instance of a common problem in recommender systems: using a database of book reviews to inform user-targeted recommendations. In our dataset, books are ca…
Scaling Text with the Class Affinity Model
Patrick O. Perry, Kenneth Benoit
Probabilistic methods for classifying text form a rich tradition in machine learning and natural language processing. For many important problems, however, class prediction is unin…
Estimating the number of clusters using cross-validation
Wei Fu, Patrick O. Perry
Many clustering methods, including k-means, require the user to specify the number of clusters as an input parameter. A variety of methods have been devised to choose the number of…
Fast Moment-Based Estimation for Hierarchical Models
Patrick O. Perry
Hierarchical models allow for heterogeneous behaviours in a population while simultaneously borrowing estimation strength across all subpopulations. Unfortunately, existing likelih…
Degrees of freedom for combining regression with factor analysis
Patrick O. Perry, Natesh S. Pillai
In the AGEMAP genomics study, researchers were interested in detecting genes related to age in a variety of tissue types. After not finding many age-related genes in some of the an…
Profile Likelihood Biclustering
Cheryl J. Flynn, Patrick O. Perry
Biclustering, the process of simultaneously clustering the rows and columns of a data matrix, is a popular and effective tool for finding structure in a high-dimensional dataset. M…