The Recurrent Sticky Hierarchical Dirichlet Process Hidden Markov Model
| Title: | The Recurrent Sticky Hierarchical Dirichlet Process Hidden Markov Model |
|---|---|
| Authors: | Słupiński, Mikołaj, Lipiński, Piotr |
| Publication Year: | 2024 |
| Collection: | Computer Science Mathematics Statistics |
| Subject Terms: | Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Mathematics - Dynamical Systems, Statistics - Machine Learning |
| More Details: | The Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) is a natural Bayesian nonparametric extension of the classical Hidden Markov Model for learning from (spatio-)temporal data. A sticky HDP-HMM has been proposed to strengthen the self-persistence probability in the HDP-HMM. Then, disentangled sticky HDP-HMM has been proposed to disentangle the strength of the self-persistence prior and transition prior. However, the sticky HDP-HMM assumes that the self-persistence probability is stationary, limiting its expressiveness. Here, we build on previous work on sticky HDP-HMM and disentangled sticky HDP-HMM, developing a more general model: the recurrent sticky HDP-HMM (RS-HDP-HMM). We develop a novel Gibbs sampling strategy for efficient inference in this model. We show that RS-HDP-HMM outperforms disentangled sticky HDP-HMM, sticky HDP-HMM, and HDP-HMM in both synthetic and real data segmentation. |
| Document Type: | Working Paper |
| Access URL: | http://arxiv.org/abs/2411.04278 |
| Accession Number: | edsarx.2411.04278 |
| Database: | arXiv |
| FullText | Text: Availability: 0 CustomLinks: – Url: http://arxiv.org/abs/2411.04278 Name: EDS - Arxiv Category: fullText Text: View this record from Arxiv MouseOverText: View this record from Arxiv – Url: https://resolver.ebsco.com/c/xy5jbn/result?sid=EBSCO:edsarx&genre=article&issn=&ISBN=&volume=&issue=&date=20241106&spage=&pages=&title=The Recurrent Sticky Hierarchical Dirichlet Process Hidden Markov Model&atitle=The%20Recurrent%20Sticky%20Hierarchical%20Dirichlet%20Process%20Hidden%20Markov%20Model&aulast=S%C5%82upi%C5%84ski%2C%20Miko%C5%82aj&id=DOI: Name: Full Text Finder (for New FTF UI) (s8985755) Category: fullText Text: Find It @ SCU Libraries MouseOverText: Find It @ SCU Libraries |
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| RecordInfo | BibRecord: BibEntity: Subjects: – SubjectFull: Computer Science - Machine Learning Type: general – SubjectFull: Computer Science - Artificial Intelligence Type: general – SubjectFull: Mathematics - Dynamical Systems Type: general – SubjectFull: Statistics - Machine Learning Type: general Titles: – TitleFull: The Recurrent Sticky Hierarchical Dirichlet Process Hidden Markov Model Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Słupiński, Mikołaj – PersonEntity: Name: NameFull: Lipiński, Piotr IsPartOfRelationships: – BibEntity: Dates: – D: 06 M: 11 Type: published Y: 2024 |
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