Sparse clustering via the Deterministic Information Bottleneck algorithm
Fuente:
arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866914465601028096 |
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| author | Costa, Efthymios Papatsouma, Ioanna Markos, Angelos |
| author_facet | Costa, Efthymios Papatsouma, Ioanna Markos, Angelos |
| contents | Cluster analysis relates to the task of assigning objects into groups which ideally present some desirable characteristics. When a cluster structure is confined to a subset of the feature space, traditional clustering techniques face unprecedented challenges. We present an information theoretic framework that overcomes the problems associated with sparse data, allowing for joint feature weighting and clustering. Our proposal constitutes a competitive alternative to existing clustering algorithms for sparse data, as demonstrated through simulations on synthetic data. The effectiveness of our method is established by an application on a real-world genomics data set. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_20628 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Sparse clustering via the Deterministic Information Bottleneck algorithm Costa, Efthymios Papatsouma, Ioanna Markos, Angelos Machine Learning 62H30 Cluster analysis relates to the task of assigning objects into groups which ideally present some desirable characteristics. When a cluster structure is confined to a subset of the feature space, traditional clustering techniques face unprecedented challenges. We present an information theoretic framework that overcomes the problems associated with sparse data, allowing for joint feature weighting and clustering. Our proposal constitutes a competitive alternative to existing clustering algorithms for sparse data, as demonstrated through simulations on synthetic data. The effectiveness of our method is established by an application on a real-world genomics data set. |
| title | Sparse clustering via the Deterministic Information Bottleneck algorithm |
| topic | Machine Learning 62H30 |
| url | https://arxiv.org/abs/2601.20628 |