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Wojciech Nadara

Publications and source records attributed to Wojciech Nadara.

20 records · Page 2Linked to original sources

Improved bounds for the excluded-minor approximation of treedepth

Treedepth, a more restrictive graph width parameter than treewidth and pathwidth, plays a major role in the theory of sparse graph classes. We show that there exists a constant $C$ such that for every positive integers $a,b$ and a graph $G$, if the treedepth of $G$ is at least $Cab$, then the treewidth of $G$ is at least $a$ or $G$ contains a subcubic (i.e., of maximum degree at most $3$) tree of treedepth at least $b$ as a subgraph. As a direct corollary, we obtain that every graph of treedepth $Ω(k^3)$ is either of treewidth at least $k$, contains a subdivision of full binary tree of depth $k$, or contains a path of length $2^k$. This improves the bound of $Ω(k^5 \log^2 k)$ of Kawarabayashi and Rossman [SODA 2018]. We also show an application of our techniques for approximation algorithms of treedepth: given a graph $G$ of treedepth $k$ and treewidth $t$, one can in polynomial time compute a treedepth decomposition of $G$ of width $\mathcal{O}(kt \log^{3/2} t)$. This improves upon a bound of $\mathcal{O}(kt^2 \log t)$ stemming from a tradeoff between known results. The main technical ingredient in our result is a proof that every tree of treedepth $d$ contains a subcubic subtree of treedepth at least $d \cdot \log_3 ((1+\sqrt{5})/2)$.

cs.DM↗

Experimental evaluation of kernelization algorithms to Dominating Set

The theoretical notions of graph classes with bounded expansion and that are nowhere dense are meant to capture structural sparsity of real world networks that can be used to design efficient algorithms. In the area of sparse graphs, the flagship problems are Dominating Set and its generalization r-Dominating Set. They have been precursors for model checking of first order logic on sparse graph classes. On class of graphs of bounded expansions the r-Dominating Set problem admits a constant factor approximation, a fixed-parameter algorithm, and an efficient preprocessing routine: the so-called linear kernel. This should be put in constrast with general graphs where Dominating Set is APX-hard and W[2]-complete. In this paper we provide an experimental evaluation of kernelization algorithm for Dominating Set in sparse graph classes and compare it with previous approaches designed to the preprocessing for Dominating Set.

cs.DS↗