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 "on the parameterized complexity of reconfiguration of connected dominating sets"):
  Abstract: In a reconfiguration version of an optimization problem $\mathcal{Q}$ the input is an instance of $\mathcal{Q}$ and two feasible solutions $S$ and $T$. The objective is to determine whether there exists a step-by-step transformation between $S$ and $T$ such that all intermediate steps also constitute feasible solutions. In this work, we study the parameterized complexity of the \textsc{Connected Dominating Set Reconfiguration} problem (\textsc{CDS-R)}. It was shown in previous work that the \textsc{Dominating Set Reconfiguration} problem (\textsc{DS-R}) parameterized by $k$, the maximum allowed size of a dominating set in a reconfiguration sequence, is fixed-parameter tractable on all graphs that exclude a biclique $K_{d,d}$ as a subgraph, for some constant $d \geq 1$. We show that the additional connectivity constraint makes the problem much harder, namely, that \textsc{CDS-R} is \textsf{W}$[1]$-hard parameterized by $k+\ell$, the maximum allowed size of a dominating set plus the length of the reconfiguration sequence, already on $5$-degenerate graphs. On the positive side, we show that \textsc{CDS-R} parameterized by $k$ is fixed-parameter tractable, and in fact admits a polynomial kernel on planar graphs.

Includes members:
  Member "empirical evaluation of approximation algorithms for generalized graph coloring and uniform quasi wideness":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a color avoiding approach to subgraph counting in bounded expansion classes")
  Member "reconfiguration on nowhere dense graph classes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "empirical evaluation of approximation algorithms for generalized graph coloring and uniform quasi wideness")
  Member "polynomial kernels and wideness properties of nowhere dense graph classes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a general kernelization technique for domination and independence problems in sparse classes")
  Member "neighborhood complexity and kernelization for nowhere dense classes of graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "domination above r independence does sparseness help")
  Member "reconfiguration of dominating sets":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "dominating sets reconfiguration under token sliding")
  Member "kernelization using structural parameters on sparse graph classes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "scalable kernelization for maximum independent sets")
  Member "deciding first order properties of nowhere dense graphs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "hitting topological minors is fpt")
  Member "the complexity of change":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "dominating sets reconfiguration under token sliding")

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.DS(Data Structures and Algorithms)