Semi-supervised clustering via information-theoretic markov chain aggregation

Author:

Steger Sophie1,Geiger Bernhard C.2,Śmieja Marek3

Affiliation:

1. Graz University of Technology, Graz, Austria

2. Know-Center GmbH, Graz, Austria

3. Jagiellonian University, Krakow, Poland

Funder

iDev40 (ECSEL Joint Undertaking)

HiDALGO project (H2020 Programme)

Publisher

ACM

Reference14 articles.

1. Pairwise clustering based on the mutual-information criterion

2. A Generalized Framework For Kullback–Leibler Markov Aggregation

3. D. Dua and C. Graff. 2017. UCI Machine Learning Repository. http://archive.ics.uci.edu/ml D. Dua and C. Graff. 2017. UCI Machine Learning Repository. http://archive.ics.uci.edu/ml

4. Rmixmod: TheRPackage of the Model-Based Unsupervised, Supervised, and Semi-Supervised ClassificationMixmodLibrary

5. Clustering with Partition Level Side Information

Cited by 2 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. Semi-supervised and un-supervised clustering: A review and experimental evaluation;Information Systems;2023-03

2. Semi-supervised clustering via information-theoretic markov chain aggregation;Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing;2022-04-25

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