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Pitman–Yor process
Known as:
Pitman-Yor distribution
, Pitman-Yor process
, Pitman–Yor distribution
In probability theory, a Pitman–Yor process denoted PY(d, θ, G0), is a stochastic process whose sample path is a probability distribution. A random…
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Related topics
Related topics
2 relations
Latent Dirichlet allocation
Stochastic process
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2019
2019
Bottom-Up Unsupervised Word Discovery via Acoustic Units
Saurabhchand Bhati
,
Chunxi Liu
,
J. Villalba
,
J. Trmal
,
S. Khudanpur
,
N. Dehak
IEEE Global Conference on Signal and Information…
2019
Corpus ID: 210972323
Unsupervised term discovery is the task of identifying and grouping reoccurring word-like patterns from the untranscribed audio…
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2018
2018
Short text clustering based on Pitman-Yor process mixture model
Jipeng Qiang
,
Yun Li
,
Yunhao Yuan
,
Xindong Wu
Applied intelligence (Boston)
2018
Corpus ID: 24275548
For finding the appropriate number of clusters in short text clustering, models based on Dirichlet Multinomial Mixture (DMM…
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2014
2014
Parallel Markov Chain Monte Carlo for Pitman-Yor Mixture Models
Kumar Avinava Dubey
,
Sinead Williamson
,
E. Xing
Conference on Uncertainty in Artificial…
2014
Corpus ID: 14330450
The Pitman-Yor process provides an elegant way to cluster data that exhibit power law behavior, where the number of clusters is…
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2012
2012
The Kernel Pitman-Yor Process
S. Chatzis
,
Dimitrios Korkinof
,
Y. Demiris
arXiv.org
2012
Corpus ID: 17342327
In this work, we propose the kernel Pitman-Yor process (KPYP) for nonparametric clustering of data with general spatial or…
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Highly Cited
2010
Highly Cited
2010
Topic models with power-law using Pitman-Yor process
Issei Sato
,
Hiroshi Nakagawa
Knowledge Discovery and Data Mining
2010
Corpus ID: 7681634
One important approach for knowledge discovery and data mining is to estimate unobserved variables because latent variables can…
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2009
2009
A parallel training algorithm for hierarchical pitman-yor process language models
Songfang Huang
,
S. Renals
Interspeech
2009
Corpus ID: 11069028
The Hierarchical Pitman Yor Process Language Model (HPYLM) is a Bayesian language model based on a nonparametric prior, the…
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Highly Cited
2008
Highly Cited
2008
Shared Segmentation of Natural Scenes Using Dependent Pitman-Yor Processes
Erik B. Sudderth
,
Michael I. Jordan
Neural Information Processing Systems
2008
Corpus ID: 8393812
We develop a statistical framework for the simultaneous, unsupervised segmentation and discovery of visual object categories from…
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2008
2008
Bayesian Modeling of Dependency Trees Using Hierarchical Pitman-Yor Priors
Hanna M. Wallach
,
Charles Sutton
,
A. McCallum
2008
Corpus ID: 6419565
In this paper, we describe two hierarchical Bayesian models for dependency trees. First, we show that Eisner’s classic generative…
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2005
2005
Numerical Valuation of American Options Under the CGMY Process
A. Almendral
2005
Corpus ID: 18175622
American put options written on an underlying stock following a Carr-Madan-Geman-Yor (CGMY) process are considered. It is known…
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2004
2004
Modeling the Volatility and Expected Value of a Diversified World Index
E. Platen
2004
Corpus ID: 18348899
This paper considers a diversified world stock index in a continuous financial market with the growth optimal portfolio (GOP) as…
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