Sparse Count Data Clustering Using an Exponential Approximation to Generalized Dirichlet Multinomial Distributions-Reference-Cited by-同舟云学术

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Sparse Count Data Clustering Using an Exponential Approximation to Generalized Dirichlet Multinomial Distributions

Published:2022-01 Issue:1 Volume:33 Page:89-102
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Zamzami Nuha^ORCID,Bouguila Nizar^ORCID

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software

Link

http://xplorestaging.ieee.org/ielx7/5962385/9670432/09233991.pdf?arnumber=9233991

Cited by 7 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. Dirichlet compound negative multinomial mixture models and applications;Advances in Data Analysis and Classification;2024-06-25

2. Rethinking the defense against free-rider attack from the perspective of model weight evolving frequency;Information Sciences;2024-05

3. Data Clustering with Libby-Novick Beta-Liouville Mixture Models: A Minimum Message Length Approach;Proceedings of the 2024 9th International Conference on Intelligent Information Technology;2024-02-23

4. Generalized Probabilistic Clustering Projection Models for Discrete Data;2023 International Symposium on Networks, Computers and Communications (ISNCC);2023-10-23

5. Model based clustering of multinomial count data;Advances in Data Analysis and Classification;2023-07-05

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