Bayesian Methods for Simulation Optimization

Consistency of Co-clustering exchangeable graph data

Feature allocations, probability functions, and paintboxes The problem of inferring a clustering of a data set has been the subject of much research in Bayesian analysis, and there currently exists a solid mathematical foundation for Bayesian approaches to clustering. In particular, the class of probability distributions over partitions of a data set has been characterized in a number of ways, including via exchangeable partition probability functions (EPPFs) and the Kingman paintbox. Here, we develop a generalization of the clustering problem, called feature allocation, where we allow each... Read more about MachineLearn: Tamara Broderick

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