SLShaohua Li
Shaohua Li
*This is an algorithmically generated author record based on publicly available information.
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Shaohua Li has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Dániel Marx
CISPA Helmholtz Center for Information Security, Saarbrücken, Germany
1 shared publication - Florian Hörsch
CISPA Helmholtz Center for Information Security Saarbrücken Germany
1 shared publication - Jacob Focke
CISPA Helmholtz Center for Information Security, Saarbrücken, Germany
1 shared publication
Latest Publications
- Open Access
- 22 October 2025
- Published by Springer Nature in Discrete & Computational Geometry
- Vol. 75 (2) , 537-596
Multicut Problems in Embedded Graphs: The Dependency of Complexity on the Demand Pattern
The Multicut problem asks for a minimum cut separating certain pairs of vertices: formally, given a graph G and a demand graph H on a set $$T\subseteq V(G)$$ of terminals, the task is to find a minimum-weight set C of edges of G such that whenever two vertices of T are adjacent in H , they are in different components of $$G\setminus C$$ . Colin de Verdière [ Algorithmica, 2017] showed that Multicut with t terminals on a graph G of genus g can be solved in time $$f(t,g)n^{O(\sqrt{g^2+gt+t})}$$ . Cohen-Addad et al. [ JACM , 2021] proved a matching lower bound showing that the exponent of n is essentially best possible (for every fixed value of t and g ), even in the special case of Multiway Cut , where the demand graph H is a complete graph. However, this lower bound tells us nothing about other special cases of Multicut such as Group 3-Terminal Cut (where three groups of terminals need to be separated from each other). We show that if the demand pattern is, in some sense, close to being a complete bipartite graph, then Multicut can be solved faster than $$f(t,g)n^{O(\sqrt{g^2+gt+t})}$$ , and furthermore this is the only property that allows such an improvement. Formally, for a class $$\mathcal {H}$$ of graphs, $$\textsc {Multicut}(\mathcal {H})$$ is the special case where the demand graph H is in $$\mathcal {H}$$ . For every fixed class $$\mathcal {H}$$ (satisfying some mild closure property), fixed g , and fixed t , our main result gives tight upper and lower bounds on the exponent of n in algorithms solving $$\textsc {Multicut}(\mathcal {H})$$ .- 22 October 2025
- Published by Springer Nature in Discrete & Computational Geometry
- Vol. 75 (2) , 537-596
Open AccessMulticut Problems in Embedded Graphs: The Dependency of Complexity on the Demand Pattern
The Multicut problem asks for a minimum cut separating certain pairs of vertices: formally, given a graph G and a demand graph H on a set $$T\subseteq V(G)$$ of terminals, the task is to find a minimum-weight set C of edges of G such that whenever two vertices of T are adjacent in H , they are in different components of $$G\setminus C$$ . Colin de Verdière [ Algorithmica, 2017] showed that Multicut with t terminals on a graph G of genus g can be solved in time $$f(t,g)n^{O(\sqrt{g^2+gt+t})}$$ . Cohen-Addad et al. [ JACM , 2021] proved a matching lower bound showing that the exponent of n is essentially best possible (for every fixed value of t and g ), even in the special case of Multiway Cut , where the demand graph H is a complete graph. However, this lower bound tells us nothing about other special cases of Multicut such as Group 3-Terminal Cut (where three groups of terminals need to be separated from each other). We show that if the demand pattern is, in some sense, close to being a complete bipartite graph, then Multicut can be solved faster than $$f(t,g)n^{O(\sqrt{g^2+gt+t})}$$ , and furthermore this is the only property that allows such an improvement. Formally, for a class $$\mathcal {H}$$ of graphs, $$\textsc {Multicut}(\mathcal {H})$$ is the special case where the demand graph H is in $$\mathcal {H}$$ . For every fixed class $$\mathcal {H}$$ (satisfying some mild closure property), fixed g , and fixed t , our main result gives tight upper and lower bounds on the exponent of n in algorithms solving $$\textsc {Multicut}(\mathcal {H})$$ .