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arXiv Machine Learning By Matteo Castiglioni, Anna Lunghi, Alberto Marchesi

Breaking the $T^{3/4}$ Barrier for Regret Minimization With Bi-Dimensional CDFs

Read the original on arXiv Machine Learning →

arXiv:2607. 20258v1 Announce Type: new Abstract: We study regret minimization for learning CDF-related objectives of the form \[ g(x)\cdot\mathbb{P}_{X\sim\mathcal{D}}(X\le x), \] over $[0,1]^2$, where $g$ is a known Lipschitz function and $\mathcal{D}$ is an unknown distribution.

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