Pareto-Optimal Clustering with the Primal Deterministic Information Bottleneck

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...

Cur síos iomlán

Sonraí bibleagrafaíochta
Príomhchruthaitheoirí:	Andrew K. Tan, Max Tegmark, Isaac L. Chuang
Formáid:	Alt
Teanga:	English
Foilsithe / Cruthaithe:	MDPI AG 2022-05-01
Sraith:	Entropy
Ábhair:	multi-objective optimization Pareto frontier information bottleneck
Rochtain ar líne:	https://www.mdpi.com/1099-4300/24/6/771

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