VLVadim Lozin
Vadim Lozin
*This is an algorithmically generated author record based on publicly available information.
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Vadim Lozin has a total of 149 co-authors. Here are the top co-authors by number of shared publications:
- Viktor Zamaraev
University of Liverpool UK
34 shared publications - Konrad Kazimierz Dabrowski
School of Computing, Newcastle University, Newcastle upon Tyne, UK
17 shared publications - Nicholas Korpelainen
Department of Electronics, Computing and Mathematics, University of Derby, Markeaton Street, Derby, DE22 3AW, United Kingdom
11 shared publications - Bernard Ries
Department of Informatics, University of Fribourg, Fribourg, Switzerland
10 shared publications - Bogdan Alecu
School of Computing University of Leeds Leeds UK
10 shared publications - Sergey Kitaev
Department of Mathematics and Statistics, University of Strathclyde, Glasgow, UK
10 shared publications
Latest Publications
- Open Access
- 19 December 2025
- Published by Elsevier in Discrete Applied Mathematics
- Vol. 383, 152-164
Graph problems and monotone classes
- 19 December 2025
- Published by Elsevier in Discrete Applied Mathematics
- Vol. 383, 152-164
Open AccessGraph problems and monotone classes
- 18 July 2025
- Published by Springer Nature
- p. 118-131
Monotone Classes, Even Graphs and the Hamiltonian Cycle Problem
- 18 July 2025
- Published by Springer Nature
- p. 118-131
Monotone Classes, Even Graphs and the Hamiltonian Cycle Problem
- 18 July 2025
- Published by Springer Nature
- p. 160-172
Vector Spaces of Graphs Closed Under Isomorphism
- 22 June 2024
- Published by Springer Nature
- p. 460-471
The Hamiltonian Cycle Problem and Monotone Classes
- 22 June 2024
- Published by Springer Nature
- p. 460-471
The Hamiltonian Cycle Problem and Monotone Classes
- 29 April 2024
- Published by Elsevier in Theoretical Computer Science
- Vol. 1003
Deciding atomicity of subword-closed languages
- 29 April 2024
- Published by Elsevier in Theoretical Computer Science
- Vol. 1003
Deciding atomicity of subword-closed languages
- Open Access
- 25 February 2024
- Published by Springer Nature in Graphs and Combinatorics
- Vol. 40 (2) , 1-13
Ramsey Numbers and Graph Parameters
- 25 February 2024
- Published by Springer Nature in Graphs and Combinatorics
- Vol. 40 (2) , 1-13
Open AccessRamsey Numbers and Graph Parameters
- Open Access
- 6 January 2024
- Published by Springer Nature in Results in Mathematics
- Vol. 79 (1) , 1-17
Functionality of Box Intersection Graphs
Functionality is a graph complexity measure that extends a variety of parameters, such as vertex degree, degeneracy, clique-width, or twin-width. In the present paper, we show that functionality is bounded for box intersection graphs in $$\mathbb {R}^1$$ , i.e. for interval graphs, and unbounded for box intersection graphs in $$\mathbb {R}^3$$ . We also study a parameter known as symmetric difference, which is intermediate between twin-width and functionality, and show that this parameter is unbounded both for interval graphs and for unit box intersection graphs in $$\mathbb {R}^2$$ .- 6 January 2024
- Published by Springer Nature in Results in Mathematics
- Vol. 79 (1) , 1-17
Open AccessFunctionality of Box Intersection Graphs
Functionality is a graph complexity measure that extends a variety of parameters, such as vertex degree, degeneracy, clique-width, or twin-width. In the present paper, we show that functionality is bounded for box intersection graphs in $$\mathbb {R}^1$$ , i.e. for interval graphs, and unbounded for box intersection graphs in $$\mathbb {R}^3$$ . We also study a parameter known as symmetric difference, which is intermediate between twin-width and functionality, and show that this parameter is unbounded both for interval graphs and for unit box intersection graphs in $$\mathbb {R}^2$$ . - Open Access
Functionality of box intersection graphs
Functionality is a graph complexity measure that extends a variety of parameters, such as vertex degree, degeneracy, clique-width, or twin-width. In the present paper, we show that functionality is bounded for box intersection graphs in $\mathbb{R}^1$, i.e. for interval graphs, and unbounded for box intersection graphs in $\mathbb{R}^3$. We also study a parameter known as symmetric difference, which is intermediate between twin-width and functionality, and show that this parameter is unbounded both for interval graphs and for unit box intersection graphs in $\mathbb{R}^2$.Open AccessFunctionality of box intersection graphs
Functionality is a graph complexity measure that extends a variety of parameters, such as vertex degree, degeneracy, clique-width, or twin-width. In the present paper, we show that functionality is bounded for box intersection graphs in $\mathbb{R}^1$, i.e. for interval graphs, and unbounded for box intersection graphs in $\mathbb{R}^3$. We also study a parameter known as symmetric difference, which is intermediate between twin-width and functionality, and show that this parameter is unbounded both for interval graphs and for unit box intersection graphs in $\mathbb{R}^2$. - Open Access
- 27 June 2023
- Published by Elsevier in Discrete Mathematics
- Vol. 346 (10)
Graph parameters, implicit representations and factorial properties
- 27 June 2023
- Published by Elsevier in Discrete Mathematics
- Vol. 346 (10)
Open AccessGraph parameters, implicit representations and factorial properties
- Open Access
Graph parameters, implicit representations and factorial properties
How to efficiently represent a graph in computer memory is a fundamental data structuring question. In the present paper, we address this question from a combinatorial point of view. A representation of an $n$-vertex graph $G$ is called implicit if it assigns to each vertex of $G$ a binary code of length $O(\log n)$ so that the adjacency of two vertices is a function of their codes. A necessary condition for a hereditary class $X$ of graphs to admit an implicit representation is that $X$ has at most factorial speed of growth. This condition, however, is not sufficient, as was recently shown in [Hatami & Hatami, FOCS 2022]. Several sufficient conditions for the existence of implicit representations deal with boundedness of some parameters, such as degeneracy or clique-width. In the present paper, we analyze more graph parameters and prove a number of new results related to implicit representation and factorial properties.Open AccessGraph parameters, implicit representations and factorial properties
How to efficiently represent a graph in computer memory is a fundamental data structuring question. In the present paper, we address this question from a combinatorial point of view. A representation of an $n$-vertex graph $G$ is called implicit if it assigns to each vertex of $G$ a binary code of length $O(\log n)$ so that the adjacency of two vertices is a function of their codes. A necessary condition for a hereditary class $X$ of graphs to admit an implicit representation is that $X$ has at most factorial speed of growth. This condition, however, is not sufficient, as was recently shown in [Hatami & Hatami, FOCS 2022]. Several sufficient conditions for the existence of implicit representations deal with boundedness of some parameters, such as degeneracy or clique-width. In the present paper, we analyze more graph parameters and prove a number of new results related to implicit representation and factorial properties.