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Journal ArticleDOI

Kernel(s) for problems with no kernel: On out-trees with many leaves

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TLDR
For the k-Leaf-Out-Branching problem, it was shown in this paper that no polynomial-sized kernel is possible unless coNP is in NP/poly.
Abstract
The k-Leaf Out-Branching problem is to find an out-branching, that is a rooted oriented spanning tree, with at least k leaves in a given digraph. The problem has recently received much attention from the viewpoint of parameterized algorithms. Here, we take a kernelization based approach to the k-Leaf-Out-Branching problem. We give the first polynomial kernel for Rooted k-Leaf-Out-Branching, a variant of k-Leaf-Out-Branching where the root of the tree searched for is also a part of the input. Our kernel with O(k3) vertices is obtained using extremal combinatorics.For the k-Leaf-Out-Branching problem, we show that no polynomial-sized kernel is possible unless coNP is in NP/poly. However, our positive results for Rooted k-Leaf-Out-Branching immediately imply that the seemingly intractable k-Leaf-Out-Branching problem admits a data reduction to n independent polynomial-sized kernels. These two results, tractability and intractability side by side, are the first ones separating Karp kernelization from Turing kernelization. This answers affirmatively an open problem regarding “cheat kernelization” raised by Mike Fellows and Jiong Guo independently.

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Journal ArticleDOI

On some FPT problems without polynomial Turing compressions

TL;DR: In this article , it was shown that edge clique cover, integer linear programming, and a -choosability parameterized by some structural parameters are NP-hard under Cook reductions even if their parameter values are small.
Posted Content

How heavy independent sets help to find arborescences with many leaves in DAGs

TL;DR: In this paper, a 7/5-approximation algorithm for the maximum leaf spanning arborescence problem on rooted directed acyclic graphs was proposed, which is the best known algorithm for this problem.
Journal ArticleDOI

Introducing lop-Kernels: A Framework for Kernelization Lower Bounds

TL;DR: In this paper , it was shown that the trivial quadratic kernel for MMVC is essentially optimal, answering a question of Boria et al. (2015) , and that the known cubic kernel for maximum minimal feedback vertex set is also essentially optimal.
References
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Reducibility Among Combinatorial Problems.

TL;DR: Throughout the 1960s I worked on combinatorial optimization problems including logic circuit design with Paul Roth and assembly line balancing and the traveling salesman problem with Mike Held, which made me aware of the importance of distinction between polynomial-time and superpolynomial-time solvability.
Book

Parameterized Complexity

TL;DR: An approach to complexity theory which offers a means of analysing algorithms in terms of their tractability, and introduces readers to new classes of algorithms which may be analysed more precisely than was the case until now.
Book

Parameterized complexity theory

Jörg Flum, +1 more
TL;DR: Fixed-Parameter Tractability.
Book

Invitation to fixed-parameter algorithms

TL;DR: This paper discusses Fixed-Parameter Algorithms, Parameterized Complexity Theory, and Selected Case Studies, and some of the techniques used in this work.
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