Markovletics: Methods and A Novel Application for Learning Continuous-Time Markov Chain Mixtures-Reference-Cited by-同舟云学术

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Markovletics: Methods and A Novel Application for Learning Continuous-Time Markov Chain Mixtures

Published:2024-05-13 Issue: Volume:28 Page:4160-4171
ISSN:
Container-title:Proceedings of the ACM Web Conference 2024
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Author:

Spaeh Fabian¹^ORCID,Tsourakakis Charalampos E.¹^ORCID

Affiliation:

1. Boston University, Boston, MA, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3589334.3645491

Reference50 articles.

1. 2023. Anonymous code repository. Available at https://github.com/285714/WWW2024.

2. Accessed Oct. 2023. Lastfm dataset. Available at https://zenodo.org/record/6090214 and sourced from https://www.last.fm/.

3. Animashree Anandkumar, Daniel Hsu, and Sham M Kakade. 2012. A method of moments for mixture models and hidden Markov models. In Conference on Learning Theory. JMLR Workshop and Conference Proceedings, 33--1.

4. William J Anderson. 2012. Continuous-time Markov chains: An applications-oriented approach. Springer Science & Business Media.

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