human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "polynomial kernels and wideness properties of nowhere dense graph classes"):
  Abstract: Nowhere dense classes of graphs are very general classes of uniformly sparse graphs with several seemingly unrelated characterisations. From an algorithmic perspective, a characterisation of these classes in terms of uniform quasi-wideness, a concept originating in finite model theory, has proved to be particularly useful. Uniform quasi-wideness is used in many fpt-algorithms on nowhere dense classes. However, the existing constructions showing the equivalence of nowhere denseness and uniform quasi-wideness imply a non-elementary blow up in the parameter dependence of the fpt-algorithms, making them infeasible in practice. #R##N#As a first main result of this paper, we use tools from logic, in particular from a subfield of model theory known as stability theory, to establish polynomial bounds for the equivalence of nowhere denseness and uniform quasi-wideness. #R##N#A powerful method in parameterized complexity theory is to compute a problem kernel in a pre-computation step, that is, to reduce the input instance in polynomial time to a sub-instance of size bounded in the parameter only (independently of the input graph size). Our new tools allow us to obtain for every fixed value of $r$ a polynomial kernel for the distance-$r$ dominating set problem on nowhere dense classes of graphs. This result is particularly interesting, as it implies that for every class $\mathcal{C}$ of graphs which is closed under subgraphs, the distance-$r$ dominating set problem admits a kernel on $\mathcal{C}$ for every value of $r$ if, and only if, it admits a polynomial kernel for every value of $r$ (under the standard assumption of parameterized complexity theory that $\mathrm{FPT} \neq W[2]$).

Includes members:
  Member "bidimensionality and kernels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hitting topological minors is fpt")
  Member "neighborhood complexity and kernelization for nowhere dense classes of graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the parameterized complexity of reconfiguration of connected dominating sets")
  Member "kernelization and sparseness the case of dominating set":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "domination above r independence does sparseness help")
  Member "kernelization using structural parameters on sparse graph classes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the parameterized complexity of reconfiguration of connected dominating sets")
  Member "deciding first order properties of nowhere dense graphs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "hitting topological minors is fpt")
  Member "kernels for connected dominating set on graphs with excluded topological subgraphs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a general kernelization technique for domination and independence problems in sparse classes")
  Member "structure theorem and isomorphism test for graphs with excluded topological subgraphs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "hypergraph isomorphism for groups with restricted composition factors")
  Member "homomorphism preservation on quasi wide classes":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "empirical evaluation of approximation algorithms for generalized graph coloring and uniform quasi wideness")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.DM(Discrete Mathematics)