FastEx: Hash Clustering with Exponential Families

Clustering is a key component in data analysis toolbox. In this paper we present a sampler, capable of estimating mixtures of exponential families. At its heart lies a novel proposal distribution using random projections to achieve high throughput in generating proposals, which is crucial for clustering models with large numbers of clusters. Papers published at the Neural Information Processing Systems Conference.