arXiv:2504.10428v2 Announce Type: replace
Abstract: Binary classification from positive-only samples is a variant of PAC learning where the learner receives i.i.d. positive samples and aims to learn a classifier with low error. Previous work by Natara…
arXiv:2410.01656v2 Announce Type: replace-cross
Abstract: We study the estimation of distributional parameters when samples are shown only if they fall in some unknown set $S \subseteq \mathbb{R}^d$. Kontonis, Tzamos, and Zampetakis (FOCS’19) gave a $…
arXiv:2605.08072v1 Announce Type: new
Abstract: $L_1$-Approximating polynomials, i.e., polynomials that approximate indicator functions in $L_1$-norm under certain distributions, are widely used in computational learning theory. We study the existence…