English

A Note on How to Remove the $\ln\ln T$ Term from the Squint Bound

Machine Learning 2026-04-30 v1 Optimization and Control Machine Learning

Abstract

In Orabona and P\'al [2016], we introduced the shifted KT potentials, to remove the lnlnT\ln \ln T factor in the parameter-free learning with expert bound. In this short technical note, I show that this is equivalent to changing the prior in the Krichevsky--Trofimov algorithm. Then, I show how to use the same idea to remove the lnlnT\ln \ln T factor in the data-independent bound for the Squint algorithm.

Keywords

Cite

@article{arxiv.2604.26926,
  title  = {A Note on How to Remove the $\ln\ln T$ Term from the Squint Bound},
  author = {Francesco Orabona},
  journal= {arXiv preprint arXiv:2604.26926},
  year   = {2026}
}