190 citations · 789 across the 22 of their papers we have counts for
26 papers
Estimation of Gaussian Bi-Clusters with General Block-Diagonal Covariance Matrix and Applications
Anastasiia Livochka, Ryan Browne, Sanjeena Subedi
Bi-clustering is a technique that allows for the simultaneous clustering of observations and features in a dataset. This technique is often used in bioinformatics, text mining, and…
One Line To Rule Them All: Generating LO-Shot Soft-Label Prototypes
Ilia Sucholutsky, Nam-Hwui Kim, Ryan P. Browne +1
Increasingly large datasets are rapidly driving up the computational costs of machine learning. Prototype generation methods aim to create a small set of synthetic observations tha…
A parsimonious family of multivariate Poisson-lognormal distributions for clustering multivariate count data
Sanjeena Subedi, Ryan Browne
Multivariate count data are commonly encountered through high-throughput sequencing technologies in bioinformatics, text mining, or in sports analytics. Although the Poisson distri…
Model-based clustering and classification using mixtures of multivariate skewed power exponential distributions
Utkarsh J. Dang, Michael P. B. Gallaugher, Ryan P. Browne +1
Families of mixtures of multivariate power exponential (MPE) distributions have been previously introduced and shown to be competitive for cluster analysis in comparison to other e…
Mixtures of Hidden Truncation Hyperbolic Factor Analyzers
Paula M. Murray, Ryan P. Browne, Paul D. McNicholas
The mixture of factor analyzers model was first introduced over 20 years ago and, in the meantime, has been extended to several non-Gaussian analogues. In general, these analogues…
Hidden Truncation Hyperbolic Distributions, Finite Mixtures Thereof, and Their Application for Clustering
Paula M. Murray, Ryan P. Browne, Paul D. McNicholas
A hidden truncation hyperbolic (HTH) distribution is introduced and finite mixtures thereof are applied for clustering. A stochastic representation of the HTH distribution is given…