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 "subset feedback vertex set is fixed parameter tractable"):
  Abstract: The classical Feedback Vertex Set problem asks, for a given undirected graph G and an integer k, to find a set of at most k vertices that hits all the cycles in the graph G. Feedback Vertex Set has attracted a large amount of research in the parameterized setting, and subsequent kernelization and fixed-parameter algorithms have been a rich source of ideas in the field. #R##N#In this paper we consider a more general and difficult version of the problem, named Subset Feedback Vertex Set (SUBSET-FVS in short) where an instance comes additionally with a set S ? V of vertices, and we ask for a set of at most k vertices that hits all simple cycles passing through S. Because of its applications in circuit testing and genetic linkage analysis SUBSET-FVS was studied from the approximation algorithms perspective by Even et al. [SICOMP'00, SIDMA'00]. #R##N#The question whether the SUBSET-FVS problem is fixed-parameter tractable was posed independently by Kawarabayashi and Saurabh in 2009. We answer this question affirmatively. We begin by showing that this problem is fixed-parameter tractable when parametrized by |S|. Next we present an algorithm which reduces the given instance to 2^k n^O(1) instances with the size of S bounded by O(k^3), using kernelization techniques such as the 2-Expansion Lemma, Menger's theorem and Gallai's theorem. These two facts allow us to give a 2^O(k log k) n^O(1) time algorithm solving the Subset Feedback Vertex Set problem, proving that it is indeed fixed-parameter tractable.

Includes members:
  Member "slightly superexponential parameterized problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the complexity of finding large odd induced subgraphs and odd colorings")
  Member "on feedback vertex set new measure and new structures":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "hitting long directed cycles is fixed parameter tractable")
  Member "solving connectivity problems parameterized by treewidth in single exponential time":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hamiltonian cycle parameterized by treedepth in single exponential time and polynomial space")
  Member "compression via matroids a randomized polynomial kernel for odd cycle transversal":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "parameterized algorithms and data reduction for the short secluded s t path problem")
  Member "on multiway cut parameterized above lower bounds":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "structural parameterizations with modulator oblivion")
  Member "multicut is fpt":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "parameterized inapproximability for steiner orientation by gap amplification")
  Member "fixed parameter tractability of multicut parameterized by the size of the cutset":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the computational complexity of finding temporal paths under waiting time constraints")
  Member "randomized algorithms for the loop cutset problem":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "hitting topological minors is fpt")

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)