Simple online learning with consistent oracle

Alexander Kozachinskiy, Tomasz Steifer
8/15/2023
cs.LGcs.AIstat.ML

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Abstract

We consider online learning in the model where a learning algorithm can access the class only via the \emph{consistent oracle} -- an oracle, that, at any moment, can give a function from the class that agrees with all examples seen so far. This model was recently considered by Assos et al.~(COLT'23). It is motivated by the fact that standard methods of online learning rely on computing the Littlestone dimension of subclasses, a computationally intractable problem. Assos et al.~gave an online learning algorithm in this model that makes at most $C^d$ mistakes on classes of Littlestone dimension $d$, for some absolute unspecified constant $C > 0$. We give a novel algorithm that makes at most $O(256^d)$ mistakes. Our proof is significantly simpler and uses only very basic properties of the Littlestone dimension. We also show that there exists no algorithm in this model that makes less than $3^d$ mistakes.

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Cite this paper

@article{kozachinskiy2023simple,
  title  = {Simple online learning with consistent oracle},
  author = {Alexander Kozachinskiy and Tomasz Steifer},
  year   = {2023},
  eprint = {2308.08055},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2308.08055v2}
}

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