Component Splitting-based Approach for Multivariate Beta Mixture Models Learning-Reference-Cited by-同舟云学术

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Component Splitting-based Approach for Multivariate Beta Mixture Models Learning

Published:2019-11 Issue: Volume: Page:
ISSN:
Container-title:2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP)
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Author:

Manouchehri Narges,Nguyen Hieu,Bouguila Nizar

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8961038/8969075/08969368.pdf?arnumber=8969368

Cited by 9 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Flexible and Hybrid Feature Mapping Technique Based on multivariate Beta Distribution Kernel Applied to Medical Applications;2022 IEEE International Conference on Industrial Technology (ICIT);2022-08-22

2. Recursive Parameter Estimation of Beta-Liouville Hidden Markov Models;2022 International Conference on Electrical, Computer and Energy Technologies (ICECET);2022-07-20

3. Batch and Online Variational Learning of Hierarchical Pitman-Yor Mixtures of Multivariate Beta Distributions;2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA);2021-12

4. Batch and online variational learning of hierarchical Dirichlet process mixtures of multivariate Beta distributions in medical applications;Pattern Analysis and Applications;2021-09-06

5. A Nonparametric Bayesian Framework for Multivariate Beta Mixture Models;2021 IEEE 22nd International Conference on Information Reuse and Integration for Data Science (IRI);2021-08

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