In this paper we consider the problem of finding a maximum weight set subject to a k-extendible constraint in the data stream model. The only non-trivial algorithm known for this problem to date---to the best of our knowledge---is a semi-streaming k2(1+ε)-approximation algorithm (Crouch and Stubbs, 2014), but semi-streaming O(k)-approximation algorithms are known for many restricted cases of this general problem. In this paper, we close most of this gap by presenting a semi-streaming O(klogk)-approximation algorithm for the general problem, which is almost the best possible even in the offline setting (Feldman et al., 2017).
@article{arxiv.1906.04449,
title = {Almost Optimal Semi-streaming Maximization for k-Extendible Systems},
author = {Moran Feldman and Ran Haba},
journal= {arXiv preprint arXiv:1906.04449},
year = {2019}
}