English

Algorithms for the Generalized Poset Sorting Problem

Data Structures and Algorithms 2023-07-18 v2

Abstract

We consider a generalized poset sorting problem (GPS), in which we are given a query graph G=(V,E)G = (V, E) and an unknown poset P(V,)\mathcal{P}(V, \prec) that is defined on the same vertex set VV, and the goal is to make as few queries as possible to edges in GG in order to fully recover P\mathcal{P}, where each query (u,v)(u, v) returns the relation between u,vu, v, i.e., uvu \prec v, vuv \prec u or u≁vu \not \sim v. This generalizes both the poset sorting problem [Faigle et al., SICOMP 88] and the generalized sorting problem [Huang et al., FOCS 11]. We give algorithms with O~(npoly(k))\tilde{O}(n\cdot \mathrm{poly}(k)) query complexity when GG is a complete bipartite graph or GG is stochastic under the \ER model, where kk is the \emph{width} of the poset, and these generalize [Daskalakis et al., SICOMP 11] which only studies complete graph GG. Both results are based on a unified framework that reduces the poset sorting to partitioning the vertices with respect to a given pivot element, which may be of independent interest. Our study of GPS also leads to a new O~(n11/(2W))\tilde{O}(n^{1 - 1 / (2W)}) competitive ratio for the so-called weighted generalized sorting problem where WW is the number of distinct weights in the query graph. This problem was considered as an open question in [Charikar et al., JCSS 02], and our result makes important progress as it yields the first nontrivial sublinear ratio for general weighted query graphs (for any bounded WW). We obtain this via an O~(nk+n1.5)\tilde{O}(nk + n^{1.5}) query complexity algorithm for the case where every edge in GG is guaranteed to be comparable in the poset, which generalizes a O~(n1.5)\tilde{O}(n^{1.5}) bound for generalized sorting [Huang et al., FOCS 11].

Keywords

Cite

@article{arxiv.2304.01623,
  title  = {Algorithms for the Generalized Poset Sorting Problem},
  author = {Shaofeng H. -C. Jiang and Wenqian Wang and Yubo Zhang and Yuhao Zhang},
  journal= {arXiv preprint arXiv:2304.01623},
  year   = {2023}
}