Skip to main content

Dirichlet process mixture models with multiple modalities

Publication ,  Journal Article
Paisley, J; Carin, L
Published in: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
September 23, 2009

The Dirichlet process can be used as a nonparametric prior for an infinite-dimensional probability mass function on the parameter space of a mixture model. The set of parameters over which it is defined is generally used for a single, parametric distribution. We extend this idea to parameter spaces that characterize multiple distributions, or modalities. In this framework, observations containing multiple, incompatible pieces of information can be mixed upon, allowing for all information to inform the final clustering result. We provide a general MCMC sampling scheme and demonstrate this framework on a Gaussian-HMM mixture model applied to synthetic and Major League Baseball data. ©2009 IEEE.

Duke Scholars

Published In

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

DOI

ISSN

1520-6149

Publication Date

September 23, 2009

Start / End Page

1613 / 1616
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Paisley, J., & Carin, L. (2009). Dirichlet process mixture models with multiple modalities. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 1613–1616. https://doi.org/10.1109/ICASSP.2009.4959908
Paisley, J., and L. Carin. “Dirichlet process mixture models with multiple modalities.” ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, September 23, 2009, 1613–16. https://doi.org/10.1109/ICASSP.2009.4959908.
Paisley J, Carin L. Dirichlet process mixture models with multiple modalities. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. 2009 Sep 23;1613–6.
Paisley, J., and L. Carin. “Dirichlet process mixture models with multiple modalities.” ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Sept. 2009, pp. 1613–16. Scopus, doi:10.1109/ICASSP.2009.4959908.
Paisley J, Carin L. Dirichlet process mixture models with multiple modalities. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. 2009 Sep 23;1613–1616.

Published In

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

DOI

ISSN

1520-6149

Publication Date

September 23, 2009

Start / End Page

1613 / 1616