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Kernelization investigates exact preprocessing algorithms with performance guarantees. The most prevalent type of parameters used in kernelization is the solution size for optimization problems; however, also structural parameters have been…

Data Structures and Algorithms · Computer Science 2015-07-21 Eduard Eiben , Robert Ganian , Stefan Szeider

A stable cutset in a graph $G$ is a set $S\subseteq V(G)$ such that vertices of $S$ are pairwise non-adjacent and such that $G-S$ is disconnected, i.e., it is both stable (or independent) set and a cutset (or separator). Unlike general…

Data Structures and Algorithms · Computer Science 2024-07-03 Stefan Kratsch , Van Bang Le

The Odd Cycle Transversal problem (OCT) asks whether a given graph can be made bipartite (i.e., 2-colorable) by deleting at most l vertices. We study structural parameterizations of OCT with respect to their polynomial kernelizability,…

Data Structures and Algorithms · Computer Science 2011-07-20 Bart M. P. Jansen , Stefan Kratsch

Matroids, particularly linear ones, have been a powerful tool in parameterized complexity for algorithms and kernelization. They have sped up or replaced dynamic programming. Delta-matroids generalize matroids by encapsulating structures…

Data Structures and Algorithms · Computer Science 2025-02-20 Eduard Eiben , Tomohiro Koana , Magnus Wahlström

Assuming the AND-distillation conjecture, the Pathwidth problem of determining whether a given graph G has pathwidth at most k admits no polynomial kernelization with respect to k. The present work studies the existence of polynomial…

Data Structures and Algorithms · Computer Science 2015-03-20 Hans L. Bodlaender , Bart M. P. Jansen , Stefan Kratsch

Consider the Maximum Weight Independent Set problem for rectangles: given a family of weighted axis-parallel rectangles in the plane, find a maximum-weight subset of non-overlapping rectangles. The problem is notoriously hard both in the…

Data Structures and Algorithms · Computer Science 2016-11-22 Michał Pilipczuk , Erik Jan van Leeuwen , Andreas Wiese

We introduce the cross-composition framework for proving kernelization lower bounds. A classical problem L AND/OR-cross-composes into a parameterized problem Q if it is possible to efficiently construct an instance of Q with polynomially…

Computational Complexity · Computer Science 2015-03-20 Hans L. Bodlaender , Bart M. P. Jansen , Stefan Kratsch

We introduce the entangled quantum polynomial hierarchy $\mathsf{QEPH}$ as the class of problems that are efficiently verifiable given alternating quantum proofs that may be entangled with each other. We prove $\mathsf{QEPH}$ collapses to…

Quantum Physics · Physics 2025-02-12 Sabee Grewal , Justin Yirka

Interpreting three-leaf binary trees or {\em rooted triples} as constraints yields an entailment relation, whereby binary trees satisfying some rooted triples must also thus satisfy others, and thence a closure operator, which is known to…

Data Structures and Algorithms · Computer Science 2018-07-03 Matthew P. Johnson

Low-rank approximation of kernels is a fundamental mathematical problem with widespread algorithmic applications. Often the kernel is restricted to an algebraic variety, e.g., in problems involving sparse or low-rank data. We show that…

Machine Learning · Computer Science 2023-10-02 Jason M. Altschuler , Pablo A. Parrilo

A permutation $\pi$ contains a permutation $\sigma$ as a pattern if it contains a subsequence of length $|\sigma|$ whose elements are in the same relative order as in the permutation $\sigma$. This notion plays a major role in enumerative…

Data Structures and Algorithms · Computer Science 2015-01-13 Ivan Bliznets , Marek Cygan , Pawel Komosa , Lukas Mach

The composition technique is a popular method for excluding polynomial-size problem kernels for NP-hard parameterized problems. We present a new technique exploiting triangle-based fractal structures for extending the range of applicability…

Computational Complexity · Computer Science 2017-12-27 Till Fluschnik , Danny Hermelin , André Nichterlein , Rolf Niedermeier

We discuss approximability and inapproximability in FPT-time for a large class of subset problems where a feasible solution $S$ is a subset of the input data and the value of $S$ is $|S|$. The class handled encompasses many well-known…

Computational Complexity · Computer Science 2013-10-22 Edouard Bonnet , Vangelis Th. Paschos

We prove that there is no fpt-algorithm that can approximate the dominating set problem with any constant ratio, unless FPT= W[1]. Our hardness reduction is built on the second author's recent W[1]-hardness proof of the biclique problem.…

Computational Complexity · Computer Science 2015-11-17 Yijia Chen , Bingkai Lin

There has been a large amount of interest, both in the past and particularly recently, into the power of different families of universal approximators, e.g. ReLU networks, polynomials, rational functions. However, current research has…

Machine Learning · Computer Science 2018-05-30 Frederic Koehler , Andrej Risteski

The Vertex Cover problem plays an essential role in the study of polynomial kernelization in parameterized complexity, i.e., the study of provable and efficient preprocessing for NP-hard problems. Motivated by the great variety of positive…

Computational Complexity · Computer Science 2019-05-10 Eva-Maria C. Hols , Stefan Kratsch , Astrid Pieterse

We study the parameterized complexity of the following fundamental geometric problems with respect to the dimension $d$: i) Given $n$ points in $\Rd$, compute their minimum enclosing cylinder. ii) Given two $n$-point sets in $\Rd$, decide…

Computational Geometry · Computer Science 2015-02-18 Panos Giannopoulos , Christian Knauer , Gunter Rote , Daniel Werner

Kernelization algorithms are polynomial-time reductions from a problem to itself that guarantee their output to have a size not exceeding some bound. For example, d-Set Matching for integers d>2 is the problem of finding a matching of size…

Data Structures and Algorithms · Computer Science 2018-12-10 Holger Dell , Dániel Marx

Makespan minimization (on parallel identical or unrelated machines) is arguably the most natural and studied scheduling problem. A common approach in practical algorithm design is to reduce the size of a given instance by a fast…

Data Structures and Algorithms · Computer Science 2020-03-05 Dušan Knop , Martin Koutecký

In the Planar Disjoint Paths problem, one is given an undirected planar graph with a set of $k$ vertex pairs $(s_i,t_i)$ and the task is to find $k$ pairwise vertex-disjoint paths such that the $i$-th path connects $s_i$ to $t_i$. We study…

Data Structures and Algorithms · Computer Science 2023-07-14 Michał Włodarczyk , Meirav Zehavi