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...
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| Autores principales: | , , |
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
MDPI AG
2022-05-01
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| Colección: | Entropy |
| Materias: | |
| Acceso en línea: | https://www.mdpi.com/1099-4300/24/6/771 |
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