2012
AISTATS
AISTATS 2012
Stick-Breaking Beta Processes and the Poisson Process
Abstract
We show that the stick-breaking construction of the beta process due to \citePaisley:2010 can be obtained from the characterization of the beta process as a Poisson process. Specifically, we show that the mean measure of the underlying Poisson process is equal to that of the beta process. We use this underlying representation to derive error bounds on truncated beta processes that are tighter than those in the literature. We also develop a new MCMC inference algorithm for beta processes, based in part on our new Poisson process construction.
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Interdisciplinary Bridge
— Artificial Intelligence and Machine Learning and Mathematics & Optimization
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Hot Topic Early Bird
— markov chain monte carlo
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning
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Trend Setter
— Stochastic Processes
Authors
Topics
Artificial Intelligence > Bayesian & Probabilistic > Bayesian Learning
Machine Learning > Optimization & Theory > Stochastic Processes
Machine Learning > Bayesian & Probabilistic > Bayesian Learning
Mathematics & Optimization > Mathematics > Stochastic Processes
Machine Learning > Bayesian & Probabilistic > Nonparametric Bayesian