Demo Data from EDBT 2026 / reviewers in the wild / expert
Lukás Mach
dblp:05/9088
· DBLP profile ↗
5ranked-venue papers
1as first author
0since 2021 · last 2020
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 4 · 1 first-authorDatabases, data management, data science and information retrieval · 1Graphics, computer vision, multimedia, augmented reality and games · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Theoretical computer science
2 papers |
Graph algorithms and graph theory · 55% Computational complexity · 45% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Graph algorithms and graph theory › graph theory › graph transformation
graph modification |
0.7 | 2 | 2020 | Lower Bounds for the Parameterized Complexity of Minimum Fill-in and Other Completion Problems · ACM Trans. Algorithms 2020 Lower bounds for the parameterized complexity of Minimum Fill-In and other completion problems · SODA 2016 |
Computational complexity
parameterized complexity |
0.7 | 2 | 2020 | Lower Bounds for the Parameterized Complexity of Minimum Fill-in and Other Completion Problems · ACM Trans. Algorithms 2020 Lower bounds for the parameterized complexity of Minimum Fill-In and other completion problems · SODA 2016 |
Computational complexity › parameterized complexity › kernelization
kernelization lower bounds |
0.4 | 1 | 2020 | Lower Bounds for the Parameterized Complexity of Minimum Fill-in and Other Completion Problems · ACM Trans. Algorithms 2020 |
Graph algorithms and graph theory › graph theory › graph transformation › graph modification
minimum fill-in |
0.4 | 1 | 2020 | Lower Bounds for the Parameterized Complexity of Minimum Fill-in and Other Completion Problems · ACM Trans. Algorithms 2020 |
Graph algorithms and graph theory › graph theory › graph transformation › graph modification
graph triangulation |
0.2 | 1 | 2016 | Lower bounds for the parameterized complexity of Minimum Fill-In and other completion problems · SODA 2016 |
Methods — techniques the papers use, named apart from their topics
subexponential-time approximation scheme · 0.2exponential time hypothesis · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Lower Bounds for the Parameterized Complexity of Minimum Fill-in and Other Completion ProblemsabstractIn this work, we focus on several completion problems for subclasses of chordal graphs: M INIMUM F ILL -I N , I NTERVAL C OMPLETION , P ROPER I NTERVAL C OMPLETION , T RIVIALLY P ERFECT C OMPLETION , and T HRESHOLD C OMPLETION . In these problems, the task is to add at most k edges to a given graph to obtain a chordal, interval, proper interval, threshold, or trivially perfect graph, respectively. We prove the following lower bounds for all these problems, as well as for the related C HAIN C OMPLETION problem: • Assuming the Exponential Time Hypothesis, none of these problems can be solved in time 2 O ( n 1/2 /log c n ) or 2 O ( k 1/4 /log c k )· n O (1) , for some integer c . • Assuming the non-existence of a subexponential-time approximation scheme for M IN B ISECTION on d -regular graphs, for some constant d , none of these problems can be solved in time 2 o ( n ) or 2 o √k) }· n O (1) . For all the aforementioned completion problems, apart from P ROPER I NTERVAL C OMPLETION , FPT algorithms with running time of the form 2 O (√ k log k ) · n O (1) are known. Thus, the second result proves that a significant improvement of any of these algorithms would lead to a surprising breakthrough in the design of approximation algorithms for M IN B ISECTION . To prove our results, we use a reduction methodology based on combining the classic approach of starting with a sparse instance of 3-S AT , prepared using the Sparsification Lemma, with the existence of almost linear-size Probabilistically Checkable Proofs. Apart from our main results, we also obtain lower bounds excluding the existence of subexponential algorithms for the O PTIMUM L INEAR A RRANGEMENT problem, as well as improved, yet still not tight, lower bounds for F EEDBACK A RC S ET IN T OURNAMENTS . Ivan Bliznets, Marek Cygan, Pawel Komosa, Michal Pilipczuk, Lukás Mach |
ACM Trans. Algorithms | 5 |
| 2016 | Lower bounds for the parameterized complexity of Minimum Fill-In and other completion problemsabstractIn this work, we focus on several completion problems for subclasses of chordal graphs: Minimum Fill-In, Interval Completion, Proper Interval Completion, Threshold Completion, and Trivially Perfect Completion. In these problems, the task is to add at most k edges to a given graph in order to obtain a chordal, interval, proper interval, threshold, or trivially perfect graph, respectively. We prove the following lower bounds for all these problems, as well as for the related Chain Completion problem: Assuming the Exponential Time Hypothesis, none of these problems can be solved in time 2O(n1/2/logcn) or 2O(k1/4/logck). nO(1) for some integer c. Assuming the non-existence of a subexponential-time approximation scheme for Min Bisection on d-regular graphs, for some constant d, none of these problems can be solved in time 2o(n) or . Ivan Bliznets, Marek Cygan, Pawel Komosa, Lukás Mach, Michal Pilipczuk |
SODA | 4 |
| 2015 | Kernelization lower bound for Permutation Pattern Matching
Ivan Bliznets, Marek Cygan, Pawel Komosa, Lukás Mach |
Inf. Process. Lett. | 4 |
| 2013 | Amalgam Width of Matroids
Lukás Mach, Tomas Toufar |
IPEC | 1 |
| 2012 | A New Lower Bound Based on Gromov's Method of Selecting Heavily Covered Points
Daniel Král, Lukás Mach, Jean-Sébastien Sereni |
Discret. Comput. Geom. | 2 |