20 citations · 22 across the 8 of their papers we have counts for
6 papers · 1 filter
Uncertainty Quantification in Bayesian Clustering
Garritt L. Page, Andrés F. Barrientos, David B. Dahl +1
Bayesian clustering methods have the widely touted advantage of providing a probabilistic characterization of uncertainty in clustering through the posterior distribution. An amazi…
Comparison and Bayesian Estimation of Feature Allocations
David B. Dahl, Devin J. Johnson, R. Jacob Andros
Feature allocation models postulate a sampling distribution whose parameters are derived from shared features. Bayesian models place a prior distribution on the feature allocation,…
The Attraction Indian Buffet Distribution
Richard L. Warr, David B. Dahl, Jeremy M. Meyer +1
We propose the attraction Indian buffet distribution (AIBD), a distribution for binary feature matrices influenced by pairwise similarity information. Binary feature matrices are u…
Cluster Analysis via Random Partition Distributions
David B. Dahl, Jacob Andros, J. Brandon Carter
Hierarchical and k-medoids clustering are deterministic clustering algorithms based on pairwise distances. Using these same pairwise distances, we propose a novel stochastic cluste…
Search Algorithms and Loss Functions for Bayesian Clustering
David B. Dahl, Devin J. Johnson, Peter Mueller
We propose a randomized greedy search algorithm to find a point estimate for a random partition based on a loss function and posterior Monte Carlo samples. Given the large size and…
Dependent Modeling of Temporal Sequences of Random Partitions
Garritt L. Page, Fernando A. Quintana, David B. Dahl
We consider the task of modeling a dependent sequence of random partitions. It is well-known that a random measure in Bayesian nonparametrics induces a distribution over random par…