What is he best known for?
The fields of study he is best known for:
- Combinatorics
- Discrete mathematics
- Algorithm
Dániel Marx focuses on Combinatorics, Discrete mathematics, Parameterized complexity, Exponential time hypothesis and Treewidth.
While working on this project, Dániel Marx studies both Combinatorics and Constraint satisfaction problem.
His research on Discrete mathematics often connects related topics like Bounded function.
His research in Parameterized complexity intersects with topics in Disjoint sets, Function and Graph.
His Exponential time hypothesis research includes elements of Linear programming, Homomorphism, Hamiltonian path and Dominating set.
He has included themes like Partial k-tree and Tree-depth in his Treewidth study.
His most cited work include:
- Parameterized Algorithms (908 citations)
- Lower bounds based on the Exponential Time Hypothesis (278 citations)
- Parameterized graph separation problems (230 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Combinatorics, Discrete mathematics, Parameterized complexity, Treewidth and Exponential time hypothesis.
His research investigates the connection with Combinatorics and areas like Bounded function which intersect with concerns in Function.
Dániel Marx integrates Discrete mathematics with Constraint satisfaction problem in his study.
The concepts of his Parameterized complexity study are interwoven with issues in Independent set, Approximation algorithm, Directed graph and Open problem.
His Treewidth study which covers Partial k-tree that intersects with Clique-sum and Tree-depth.
His Exponential time hypothesis study combines topics in areas such as Computable function, Dimension, Exponent and Dominating set.
He most often published in these fields:
- Combinatorics (71.91%)
- Discrete mathematics (50.17%)
- Parameterized complexity (43.14%)
What were the highlights of his more recent work (between 2017-2021)?
- Combinatorics (71.91%)
- Parameterized complexity (43.14%)
- Exponential time hypothesis (15.72%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Combinatorics, Parameterized complexity, Exponential time hypothesis, Upper and lower bounds and Treewidth.
In Combinatorics, Dániel Marx works on issues like Bounded function, which are connected to Time complexity.
His biological study spans a wide range of topics, including Feedback vertex set, Discrete mathematics, Open problem and Approximation algorithm.
His Discrete mathematics study combines topics from a wide range of disciplines, such as Lattice problem and Generator matrix.
His Exponential time hypothesis research is multidisciplinary, incorporating elements of Surface and Genus.
The various areas that Dániel Marx examines in his Treewidth study include Function, Theoretical computer science and Tree decomposition.
Between 2017 and 2021, his most popular works were:
- Known Algorithms on Graphs of Bounded Treewidth Are Probably Optimal (25 citations)
- Slightly Superexponential Parameterized Problems (22 citations)
- Covering a tree with rooted subtrees: parameterized and approximation algorithms (19 citations)
In his most recent research, the most cited papers focused on:
- Combinatorics
- Algorithm
- Algebra
His main research concerns Combinatorics, Parameterized complexity, Exponential time hypothesis, Treewidth and Vertex.
The Combinatorics study combines topics in areas such as Current and Upper and lower bounds.
His research in Parameterized complexity intersects with topics in Time complexity, Discrete mathematics, Lattice problem and Approximation algorithm.
His Approximation algorithm research is multidisciplinary, incorporating perspectives in Travelling salesman problem and Planar graph.
His Exponential time hypothesis research incorporates themes from Bounded function and Independent set.
His Vertex research is multidisciplinary, relying on both Tree decomposition, Homomorphism, Computable function, Exponent and Interval graph.
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