Chasing Convex Bodies and Functions with Black-Box Advice. (arXiv:2206.11780v1 [cs.LG])

We consider the problem of convex function chasing with black-box advice,
where an online decision-maker aims to minimize the total cost of making and
switching between decisions in a normed vector space, aided by black-box advice
such as the decisions of a machine-learned algorithm. The decision-maker seeks
cost comparable to the advice when it performs well, known as
$\textit{consistency}$, while also ensuring worst-case $\textit{robustness}$
even when the advice is adversarial. We first consider the common paradigm of
algorithms that switch …

advice arxiv lg