How well do SEM algorithms imitate EM algorithms? A non-asymptotic analysis for mixture models
J. Blömer, S. Brauer, K. Bujna, D. Kuntze, Advances in Data Analysis and Classification 14 (2020) 147–173.
Download
No fulltext has been uploaded.
Journal Article
| Published
| English
Author
Blömer, JohannesLibreCat;
Brauer, SaschaLibreCat;
Bujna, Kathrin;
Kuntze, Daniel
Department
Publishing Year
Journal Title
Advances in Data Analysis and Classification
Volume
14
Page
147–173
LibreCat-ID
Cite this
Blömer J, Brauer S, Bujna K, Kuntze D. How well do SEM algorithms imitate EM algorithms? A non-asymptotic analysis for mixture models. Advances in Data Analysis and Classification. 2020;14:147–173. doi:10.1007/s11634-019-00366-7
Blömer, J., Brauer, S., Bujna, K., & Kuntze, D. (2020). How well do SEM algorithms imitate EM algorithms? A non-asymptotic analysis for mixture models. Advances in Data Analysis and Classification, 14, 147–173. https://doi.org/10.1007/s11634-019-00366-7
@article{Blömer_Brauer_Bujna_Kuntze_2020, title={How well do SEM algorithms imitate EM algorithms? A non-asymptotic analysis for mixture models}, volume={14}, DOI={10.1007/s11634-019-00366-7}, journal={Advances in Data Analysis and Classification}, author={Blömer, Johannes and Brauer, Sascha and Bujna, Kathrin and Kuntze, Daniel}, year={2020}, pages={147–173} }
Blömer, Johannes, Sascha Brauer, Kathrin Bujna, and Daniel Kuntze. “How Well Do SEM Algorithms Imitate EM Algorithms? A Non-Asymptotic Analysis for Mixture Models.” Advances in Data Analysis and Classification 14 (2020): 147–173. https://doi.org/10.1007/s11634-019-00366-7.
J. Blömer, S. Brauer, K. Bujna, and D. Kuntze, “How well do SEM algorithms imitate EM algorithms? A non-asymptotic analysis for mixture models,” Advances in Data Analysis and Classification, vol. 14, pp. 147–173, 2020.
Blömer, Johannes, et al. “How Well Do SEM Algorithms Imitate EM Algorithms? A Non-Asymptotic Analysis for Mixture Models.” Advances in Data Analysis and Classification, vol. 14, 2020, pp. 147–173, doi:10.1007/s11634-019-00366-7.
Google Scholar