Entropy regularization in probabilistic clustering
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DOI: 10.1007/s10260-023-00716-y
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- Federico Camerlenghi & Antonio Lijoi & Igor Prünster, 2018. "Bayesian nonparametric inference beyond the Gibbs‐type framework," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 45(4), pages 1062-1091, December.
- Francesco Denti & Federico Camerlenghi & Michele Guindani & Antonietta Mira, 2023. "A Common Atoms Model for the Bayesian Nonparametric Analysis of Nested Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 118(541), pages 405-416, January.
- Peter J. Green & Sylvia Richardson, 2001. "Modelling Heterogeneity With and Without the Dirichlet Process," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 28(2), pages 355-375, June.
- Daiane Aparecida Zuanetti & Peter Müller & Yitan Zhu & Shengjie Yang & Yuan Ji, 2018. "Clustering distributions with the marginalized nested Dirichlet process," Biometrics, The International Biometric Society, vol. 74(2), pages 584-594, June.
- F Ascolani & A Lijoi & G Rebaudo & G Zanella, 2023. "Clustering consistency with Dirichlet process mixtures," Biometrika, Biometrika Trust, vol. 110(2), pages 551-558.
- Antonio Lijoi & Igor Prünster & Giovanni Rebaudo, 2023. "Flexible clustering via hidden hierarchical Dirichlet priors," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(1), pages 213-234, March.
- Teh, Yee Whye & Jordan, Michael I. & Beal, Matthew J. & Blei, David M., 2006. "Hierarchical Dirichlet Processes," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1566-1581, December.
- repec:dau:papers:123456789/1908 is not listed on IDEAS
- Fangzheng Xie & Yanxun Xu, 2020. "Bayesian Repulsive Gaussian Mixture Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(529), pages 187-203, January.
- Jeffrey W. Miller & Matthew T. Harrison, 2018. "Mixture Models With a Prior on the Number of Components," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(521), pages 340-356, January.
- Brenda Betancourt & Giacomo Zanella & Rebecca C. Steorts, 2022. "Random Partition Models for Microclustering Tasks," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 117(539), pages 1215-1227, September.
- Yanxun Xu & Peter Müller & Donatello Telesca, 2016. "Bayesian inference for latent biologic structure with determinantal point processes (DPP)," Biometrics, The International Biometric Society, vol. 72(3), pages 955-964, September.
- Francesco Bartolucci & Alessio Farcomeni & Luisa Scaccia, 2017. "A Nonparametric Multidimensional Latent Class IRT Model in a Bayesian Framework," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 952-978, December.
- Antonio Lijoi & Ramsés H. Mena & Igor Prünster, 2007. "Controlling the reinforcement in Bayesian non‐parametric mixture models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(4), pages 715-740, September.
- Juhee Lee & Peter Müller & Yitan Zhu & Yuan Ji, 2013. "A Nonparametric Bayesian Model for Local Clustering With Application to Proteomics," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(503), pages 775-788, September.
- Sonia Petrone & Michele Guindani & Alan E. Gelfand, 2009. "Hybrid Dirichlet mixture models for functional data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(4), pages 755-782, September.
- Matthew Stephens, 2000. "Dealing with label switching in mixture models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 795-809.
- White, Arthur & Murphy, Thomas Brendan, 2014. "BayesLCA: An R Package for Bayesian Latent Class Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 61(i13).
- David B. Dahl & Ryan Day & Jerry W. Tsai, 2017. "Random Partition Distribution Indexed by Pairwise Information," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 721-732, April.
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Keywords
Dirichlet process; Loss functions; Mixture models; Unbalanced clusters; Random partition;All these keywords.
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