Work

Applications of littlestone dimension to query learning and to compression

Year: 2026

Type: article

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.

Source: Information and Computation

DOI: 10.1016/j.ic.2026.105424

Authors: Hunter Chase, James Freitag, Lev Reyzin

Institution: University of Illinois Chicago

Language: English

Topic: Machine Learning and Algorithms

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,840

Funders: National Science Foundation, Division of Electrical, Communications and Cyber Systems