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Pareto-Optimal Clustering with the Primal Deterministic Information Bottleneck
At the heart of both lossy compression and clustering is a trade-off between the fidelity and size of the learned representation. Our goal is to map out and study the Pareto frontier that quantifies this trade-off. We focus on the optimization of the Deterministic Information Bottleneck (DIB) object...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9222302/ https://www.ncbi.nlm.nih.gov/pubmed/35741492 http://dx.doi.org/10.3390/e24060771 |