{"paper":{"title":"Online Multistage Subset Maximization Problems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CC"],"primary_cat":"cs.DS","authors_text":"Alexandre Teiller, Bruno Escoffier, Evripidis Bampis, Kevin Schewior","submitted_at":"2019-05-10T13:28:23Z","abstract_excerpt":"Numerous combinatorial optimization problems (knapsack, maximum-weight matching, etc.) can be expressed as \\emph{subset maximization problems}: One is given a ground set $N=\\{1,\\dots,n\\}$, a collection $\\mathcal{F}\\subseteq 2^N$ of subsets thereof such that $\\emptyset\\in\\mathcal{F}$, and an objective (profit) function $p:\\mathcal{F}\\rightarrow\\mathbb{R}_+$. The task is to choose a set $S\\in\\mathcal{F}$ that maximizes $p(S)$. We consider the \\emph{multistage} version (Eisenstat et al., Gupta et al., both ICALP 2014) of such problems: The profit function $p_t$ (and possibly the set of feasible s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.04162","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}