In computer science, parameterized complexity is a branch of computational complexity theory that focuses on classifying computational problems according to their inherent difficulty with respect to multiple parameters of the input or output.
Introduction. 1.1. Parameterized complexity. While classically running times or other re- sources of algorithms are measured by a function in the length of ...
Dec 22, 2011 · Parameterized complexity knows two sources of complexity, namely quantificational and propositional alternation ([26, p. 337], [37, p. 195]).
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Dec 15, 2023 · Parameterized complexity adds a finer layer to the analysis of languages than classical com- plexity theory. Classically, metrics like ...
These machine characterizations give rise to two natural notions of parameterized randomized algorithms that we call W[P]-randomization and W[1]-randomization.
In this seminar we hope to help bridge this gap, by bringing together experts in the areas of randomized algorithms and parameterized complexity.
These machine characterizations give rise to two natural notions of parameterized randomized algorithms that we call W[P]-randomization and W[1]-randomization.
Abstract. The article was prepared for the LATA 2012 conference where. I will be presenting two one and half hour lecctures for a short tutorial.
Abstract This chapter compiles a number of results that apply the theory of parameterized algorithmics to the running-time analysis of randomized search.
Parameterized Random Complexity. ... A genuinely parameterized view on random complexity would instead mean to measure random complexity using parameterizations.