Nonparametric Bayesian Inference on Multivariate Exponential Families

Nonparametric Bayesian Inference on Multivariate Exponential Families

We develop a model by choosing the maximum entropy distribution from the set of models satisfying certain smoothness and independence criteria; we show that inference on this model generalizes local kernel estimation to the context of Bayesian inference on stochastic processes. Our model enables Bay...

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Bibliographic Details
Main Authors: Vega-Brown, William R (Contributor), Doniec, Marek Wojciech (Contributor), Roy, Nicholas (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor), Massachusetts Institute of Technology. Department of Mechanical Engineering (Contributor)
Format: Article
Language:English
Published: Association for Computing Machinery (ACM), 2017-06-05T14:19:24Z.
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