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The two parameter Poisson-Dirichlet Process (PDP), a generalisation of the Dirichlet Process, is increasingly being used for probabilistic modelling in discrete areas such as language technology, bioinformatics, and image analysis.
Numeri di stirling generalizzati operatori differenziali e polinomi ipergeometrici
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A Bayesian analysis of some nonparametric problems
T. Ferguson · 1973
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Mixtures of Dirichlet processes with applications to Bayesian nonparametric problems
C.E. Antoniak · 1974
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The infinite Gaussian mixture model
C.E. Rasmussen · 2000
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Moments of some statistics of Pitman sampling formula
H. Yamato and M. Sibuya · 2000
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K. Kurihara, M. Welling, and Y. W. Teh · 2007
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Large sample asymptotics for the two-parameter Poisson-Dirichlet process
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Flexible priors for exemplar-based clustering
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Bayesian modeling of dependency trees using hierarchical Pitman-Yor priors
H. Wallach, C. Sutton, and A. McCallum · 2008
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Y. W. Teh · 2006
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A hierarchical Bayesian language model based on Pitman-Yor processes
Y.W. Teh · 2006
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Infinite hidden relational models
Z. Xu, V. Tresp, K. Yu, and H.-P. Kriegel · 2006
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Measure Theory
V. I. Bogachev · 2007
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Posterior analysis for normalized random measures with independent increments
L.F. James, A. Lijoi, and I. Prünster · 2009
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Shared segmentation of natural scenes using dependent Pitman-Yor processes
E.B. Sudderth and M. Jordan · 2009
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A stochastic memoizer for sequence data
F. Wood, C. Archambeau, J. Gasthaus, L.F. James, and Y.W. Teh · 2009
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Sampling table configurations for the hierarchical Poisson-Dirichlet process
C. Chen, L. Du, and W. Buntine · 2011
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