Results 251 to 260 of about 23,712,988 (293)

Communication-Efficient Federated Class-Incremental Intrusion Detection for Edge IoT Networks. [PDF]

Sensors (Basel)
Wu Z, He B, Si Z, Qiu C, Liao X, Su C.
europepmc   +1 more source

Analyzing the digital customer journey: a novel framework for sequential behavior modeling. [PDF]

Sci Rep
Bar-El L, Chalutz-BenGal H, Gazit S, Patalon T, Ben-Gal I.   +4 more
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Multivariate causal effects: a Bayesian causal regression factor model. [PDF]

Biometrics
Zorzetto D, Landy J, Zigler C, Parmigiani G, De Vito R.   +4 more
europepmc   +1 more source

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Clustering with label constrained Dirichlet process mixture model

Engineering Applications of Artificial Intelligence, 2022
Abstract In this paper, we present a constrained Dirichlet process mixture model with labels as side information. Specifically, the labeled information is incorporated through the use of a product partition prior to give clusters of instances with similar labels a higher prior preference.
Nurul Afiqah Burhanuddin, Mohd Bakri Adam, Kamarulzaman Ibrahim   +2 more
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A Dirichlet Process Mixture of Generalized Dirichlet Distributions for Proportional Data Modeling

IEEE Transactions on Neural Networks, 2010
In this paper, we propose a clustering algorithm based on both Dirichlet processes and generalized Dirichlet distribution which has been shown to be very flexible for proportional data modeling. Our approach can be viewed as an extension of the finite generalized Dirichlet mixture model to the infinite case.
Nizar Bouguila, Djemel Ziou
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Time-sensitive Dirichlet process mixture models

, 2018
Abstract: "We introduce Time-Sensitive Dirichlet Process Mixture models for clustering. The models allow infinite mixture components just like standard Dirichlet process mixture models. However they also have the ability to model time correlations between instances."
Zhu, Xiaojin, Ghahramani, Zoubin, Lafferty, John   +2 more
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A Dirichlet process mixture model for brain MRI tissue classification

Medical Image Analysis, 2007
Accurate classification of magnetic resonance images according to tissue type or region of interest has become a critical requirement in diagnosis, treatment planning, and cognitive neuroscience. Several authors have shown that finite mixture models give excellent results in the automated segmentation of MR images of the human normal brain.
Adelino R Ferreira da Silva
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Dirichlet Process Mixture of Mixtures Model for Unsupervised Subword Modeling

IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2018
We develop a parallelizable Markov chain Monte Carlo sampler for a Dirichlet process mixture of mixtures model. Our sampler jointly infers a codebook and clusters. The codebook is a global collection of components. Clusters are mixtures, defined over the codebook.
Michael Heck, Sakriani Sakti, Satoshi Nakamura 0001   +2 more
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A Probability for Classification Based on the Dirichlet Process Mixture Model

Journal of Classification, 2010
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ruth Fuentes-García, Ramsés H. Mena, Stephen G. Walker   +2 more
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