Several styles of Chinese cuisine were introduced in to Japan after the Meiji Restoration and Chinese dishes have become a must in high-class hotels and restaurants in modem Japan. The earliest Chinese restaurant in J...Several styles of Chinese cuisine were introduced in to Japan after the Meiji Restoration and Chinese dishes have become a must in high-class hotels and restaurants in modem Japan. The earliest Chinese restaurant in Japan, called "Yonghe," was opened in Tokyo in 1879 (the 12th year of展开更多
In this paper,we investigate the expectation of the size of the largest table in an(α,θ)-Chinese restaurant process by using and developing an idea originated in the work by Shepp,which discusses random permutation.
Chief chef of Four Seasons—Ping Baoguo Ping Baoguo,chief chef of Four Seasons Restaurant in Minzu Hotel,Beijing is a national treasure in theculinary line.He has been working for
This paper deals with the statistical modeling of latent topic hierarchies in text corpora. The height of the topic tree is assumed as fixed, while the number of topics on each level as unknown a priori and to be infe...This paper deals with the statistical modeling of latent topic hierarchies in text corpora. The height of the topic tree is assumed as fixed, while the number of topics on each level as unknown a priori and to be inferred from data. Taking a nonpara-metric Bayesian approach to this problem, we propose a new probabilistic generative model based on the nested hierarchical Dirichlet process (nHDP) and present a Markov chain Monte Carlo sampling algorithm for the inference of the topic tree structure as well as the word distribution of each topic and topic distribution of each document. Our theoretical analysis and experiment results show that this model can produce a more compact hierarchical topic structure and captures more fine-grained topic rela-tionships compared to the hierarchical latent Dirichlet allocation model.展开更多
The core of the nonparametric/semiparametric Bayesian analysis is to relax the particular parametric assumptions on the distributions of interest to be unknown and random,and assign them a prior.Selecting a suitable p...The core of the nonparametric/semiparametric Bayesian analysis is to relax the particular parametric assumptions on the distributions of interest to be unknown and random,and assign them a prior.Selecting a suitable prior therefore is especially critical in the nonparametric Bayesian fitting.As the distribution of distribution,Dirichlet process(DP)is the most appreciated nonparametric prior due to its nice theoretical proprieties,modeling flexibility and computational feasibility.In this paper,we review and summarize some developments of DP during the past decades.Our focus is mainly concentrated upon its theoretical properties,various extensions,statistical modeling and applications to the latent variable models.展开更多
文摘Several styles of Chinese cuisine were introduced in to Japan after the Meiji Restoration and Chinese dishes have become a must in high-class hotels and restaurants in modem Japan. The earliest Chinese restaurant in Japan, called "Yonghe," was opened in Tokyo in 1879 (the 12th year of
基金supported by National Natural Science Foundation of China (Grant No.10671036)the National Basic Research Program of China (Grant No.2007CB814904)
文摘In this paper,we investigate the expectation of the size of the largest table in an(α,θ)-Chinese restaurant process by using and developing an idea originated in the work by Shepp,which discusses random permutation.
文摘Chief chef of Four Seasons—Ping Baoguo Ping Baoguo,chief chef of Four Seasons Restaurant in Minzu Hotel,Beijing is a national treasure in theculinary line.He has been working for
基金Project (No. 60773180) supported by the National Natural Science Foundation of China
文摘This paper deals with the statistical modeling of latent topic hierarchies in text corpora. The height of the topic tree is assumed as fixed, while the number of topics on each level as unknown a priori and to be inferred from data. Taking a nonpara-metric Bayesian approach to this problem, we propose a new probabilistic generative model based on the nested hierarchical Dirichlet process (nHDP) and present a Markov chain Monte Carlo sampling algorithm for the inference of the topic tree structure as well as the word distribution of each topic and topic distribution of each document. Our theoretical analysis and experiment results show that this model can produce a more compact hierarchical topic structure and captures more fine-grained topic rela-tionships compared to the hierarchical latent Dirichlet allocation model.
基金supported in part by the National Natural Science Foundation of China(Grant No.11471161)the Technological Innovation Item in Jiangsu Province(No.BK2008156).
文摘The core of the nonparametric/semiparametric Bayesian analysis is to relax the particular parametric assumptions on the distributions of interest to be unknown and random,and assign them a prior.Selecting a suitable prior therefore is especially critical in the nonparametric Bayesian fitting.As the distribution of distribution,Dirichlet process(DP)is the most appreciated nonparametric prior due to its nice theoretical proprieties,modeling flexibility and computational feasibility.In this paper,we review and summarize some developments of DP during the past decades.Our focus is mainly concentrated upon its theoretical properties,various extensions,statistical modeling and applications to the latent variable models.
