Detailed Derivations of Small-Variance Asymptotics for some Hierarchical Bayesian Nonparametric Models. Huggins, J. H, Saeedi, A., & Johnson, M. J arXiv.org, 2014. Paper abstract bibtex In this note we provide detailed derivations of two versions of small-variance asymptotics for hierarchical Dirichlet process (HDP) mixture models and the HDP hidden Markov model (HDP-HMM, a.k.a. the infinite HMM). We include derivations for the probabilities of certain CRP and CRF partitions, which are of more general interest.
@article{HSJ-arXiv-2014,
Abstract = {In this note we provide detailed derivations of two versions of small-variance asymptotics for hierarchical Dirichlet process (HDP) mixture models and the HDP hidden Markov model (HDP-HMM, a.k.a. the infinite HMM). We include derivations for the probabilities of certain CRP and CRF partitions, which are of more general interest.},
Author = {Huggins, Jonathan H and Saeedi, Ardavan and Johnson, Matthew J},
Date-Added = {2015-01-06 15:35:01 +0000},
Date-Modified = {2015-01-06 16:10:37 +0000},
Journal = {arXiv.org},
Keywords = {Bayesian non-parametrics},
Title = {Detailed Derivations of Small-Variance Asymptotics for some Hierarchical Bayesian Nonparametric Models},
Url = {http://arxiv.org/abs/1501.00052},
Volume = {arXiv:1501.00052 [stat.ML]},
Year = {2014},
Bdsk-Url-1 = {http://arxiv.org/abs/1501.00052}}
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