mlsanityData to 14 Oct 2026

Effective Littlestone Dimension

arXiv 2411.15109 ↗First posted 22 Nov 2024cs.LG cs.LOcited by 3

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Abstract (arXiv)

Delle Rose et al.~(COLT'23) introduced an effective version of the Vapnik-Chervonenkis dimension, and showed that it characterizes improper PAC learning with total computable learners. In this paper, we introduce and study a similar effectivization of the notion of Littlestone dimension. Finite effective Littlestone dimension is a necessary condition for computable online learning but is not a sufficient one -- which we already establish for classes of the effective Littlestone dimension 2. However, the effective Littlestone dimension equals the optimal mistake bound for computable learners in two special cases: a) for classes of Littlestone dimension 1 and b) when the learner receives as additional information an upper bound on the numbers to be guessed. Interestingly, finite effective Littlestone dimension also guarantees that the class consists only of computable functions.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 6 of its 11 references that are in the map. First posted on arXiv 22 Nov 2024.

Builds on

6 of 11 references.

References · 6

  1. 2022On characterizations of learnability with computable learnerscited by 16
  2. 2023On Computable Online Learningcited by 12
  3. 2023Online Learning and Solving Infinite Games with an ERM Oraclecited by 11
  4. 2023Find a witness or shatter: the landscape of computable PAC learningcited by 10
  5. 2024On the Computability of Robust PAC Learningcited by 6
  6. 2023Simple online learning with consistent oraclecited by 5

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3 papers.