Applications of littlestone dimension to query learning and to compression

In this paper we give several applications of Littlestone dimension. The first is to the model of Angluin and Dohrn [1], where we extend their results for learning by equivalence queries with random counterexamples. Second, we extend that model to infinite concept classes with an additional source of randomness. Third, we give improved results on the relationship of Littlestone dimension to classes with extended d -compression schemes, proving the analog of a conjecture of Floyd and Warmuth [2] for Littlestone dimension.

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Publication Details

Journal
Information and Computation
Published
2026-02-24
DOI
https://doi.org/10.1016/j.ic.2026.105424
Primary Topic
Machine Learning and Algorithms
Type
article
Field-Weighted Citation Impact
0.00
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article

Applications of littlestone dimension to query learning and to compression

Hunter Chase, Lev Reyzin, James Frietag
Information and Computation
Machine Learning and Algorithms
article

Applications of littlestone dimension to query learning and to compression

Hunter Chase, Lev Reyzin, James Frietag
article en

Abstract

In this paper we give several applications of Littlestone dimension. The first is to the model of Angluin and Dohrn [1], where we extend their results for learning by equivalence queries with random counterexamples. Second, we extend that model to infinite concept classes with an additional source of randomness. Third, we give improved results on the relationship of Littlestone dimension to classes with extended d -compression schemes, proving the analog of a conjecture of Floyd and Warmuth [2] for Littlestone dimension.

Information and ComputationVol. 309
University of Illinois Chicago (US)
Openalex Percentile: Top 49%
Machine Learning and Algorithms
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