Results 41 to 50 of about 31,307,485 (221)
Modeling geo-homopholy in online social networks for population distribution projection [PDF]
International Journal of Crowd Science, 2017 Purpose – Projecting the population distribution in geographical regions is important for many applications such as launching marketing campaigns or enhancing the public safety in certain densely populated areas.
Yuanxing Zhang +5 more
doaj +1 more source
Unifying rational models of categorization via the hierarchical Dirichlet process
, 2019 Models of categorization make different representational assumptions, with categories being represented by prototypes, sets of exemplars, and everything in between.
Tom Griffiths +3 more
semanticscholar +1 more source
PLoS ONE, 2022 Although there are several articles that have carried out a systematic literature review of the analytical hierarchy process (AHP), many of them work with a limited number of analyzed documents.
Peter Madzík, Lukáš Falát
semanticscholar +1 more source
Efficient Clustering for Continuous Occupancy Mapping Using a Mixture of Gaussian Processes
Sensors, 2022 This paper proposes a novel method for occupancy map building using a mixture of Gaussian processes. Gaussian processes have proven to be highly flexible and accurate for a robotic occupancy mapping problem, yet the high computational complexity has been
Soohwan Kim, Jonghyuk Kim
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Proceedings of the International Conference on Applied Innovations in ITThis study proposes and validates a robust Bayesian model based on a Dirichlet process mixture of normals (DMNM) for probability density estimation and missing data imputation in multivariate datasets.
Hassan Sami, Asmaa Ayoob
doaj +1 more source
Truncated Poisson–Dirichlet approximation for Dirichlet process hierarchical models
Statistics and Computing, 2023 AbstractThe Dirichlet process was introduced by Ferguson in 1973 to use with Bayesian nonparametric inference problems. A lot of work has been done based on the Dirichlet process, making it the most fundamental prior in Bayesian nonparametric statistics.
Junyi Zhang, Angelos Dassios
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Modeling Topic and Role Information in Meetings using the Hierarchical Dirichlet Process [PDF]
, 2008 In this paper, we address the modeling of topic and role information in multiparty meetings, via a nonparametric Bayesian model called the hierarchical Dirichlet process.
Renals, Steve, Huang, Songfang
core +1 more source
Models beyond the Dirichlet process [PDF]
SSRN Electronic Journal, 2009 Bayesian nonparametric inference is a relatively young area of research and it has recently undergone a strong development. Most of its success can be explained by the considerable degree of flexibility it ensures in statistical modeling, if compared to parametric alternatives, and by the emergence of new and efficient simulation techniques that make ...
LIJOI, ANTONIO, PRUENSTER, IGOR
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Brief von Rebecka Lejeune Dirichlet an Peter Gustav Lejeune Dirichlet
BRIEF VON REBECKA LEJEUNE DIRICHLET AN PETER GUSTAV LEJEUNE DIRICHLET Brief von Rebecka Lejeune Dirichlet an Peter Gustav Lejeune Dirichlet ( -
Lejeune Dirichlet, Rebecka +1 more
core +10 more sources
Integration of Knowledge Graph Embedding Into Topic Modeling with Hierarchical Dirichlet Process
North American Chapter of the Association for Computational Linguistics, 2019 Leveraging domain knowledge is an effective strategy for enhancing the quality of inferred low-dimensional representations of documents by topic models.
Ding-Cheng Li +3 more
semanticscholar +1 more source