REVIEW 2 cited by
Progressive Algorithms for Domination and Independence
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Progressive Algorithms for Domination and Independence
read the original abstract
We consider a generic algorithmic paradigm that we call progressive exploration, which can be used to develop simple and efficient parameterized graph algorithms. We identify two model-theoretic properties that lead to efficient progressive algorithms, namely variants of the Helly property and stability. We demonstrate our approach by giving linear-time fixed-parameter algorithms for the distance-r dominating set problem (parameterized by the solution size) in a wide variety of restricted graph classes, such as powers of nowhere dense classes, map graphs, and (for $r=1$) biclique-free graphs. Similarly, for the distance-r independent set problem the technique can be used to give a linear-time fixed-parameter algorithm on any nowhere dense class. Despite the simplicity of the method, in several cases our results extend known boundaries of tractability for the considered problems and improve the best known running times.
Forward citations
Cited by 2 Pith papers
-
Dynamic domination and independence in sparse graphs
Fully dynamic polylogarithmic-time data structures for distance-r dominating-set and distance-r independent-set queries on bounded-expansion graphs, resolving the Dvořák–Tůma open question for these two problems.
-
Fatness and Flatness
Excluding a fixed graph as a fat minor forces a metric analog of uniform quasi-wideness; this bounds scatter dimension and yields EPAS-style approximation for norm k-clustering.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.