Unlabeled compression schemes exceeding the VC-dimension

DOI10.1016/j.dam.2019.09.022zbMath1432.68396arXiv1811.12471OpenAlexW2980798682WikidataQ127019546 ScholiaQ127019546MaRDI QIDQ2309557

Dömötör Pálvölgyi, Gábor Tardos

Publication date: 1 April 2020

Published in: Discrete Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1811.12471

zbMATH Keywords

learning theoryVC-dimensioncompression schemes

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Coding and information theory (compaction, compression, models of communication, encoding schemes, etc.) (aspects in computer science) (68P30)

Related Items (6)

Unlabeled sample compression schemes and corner peelings for ample and maximum classes ⋮ What convex geometries tell about shattering-extremal systems ⋮ Sample Compression Schemes for Balls in Graphs ⋮ Compression schemes for concept classes induced by three types of discrete undirected graphical models ⋮ Inclusion matrices for rainbow subsets ⋮ Unnamed Item

Cites Work

• Unnamed Item
• Sample Compression Schemes for VC Classes
• Learning Theory
• On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities

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