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 "solving problems on graphs of high rank width"):
  Abstract: A modulator of a graph G to a specified graph class H is a set of vertices whose deletion puts G into H. The cardinality of a modulator to various tractable graph classes has long been used as a structural parameter which can be exploited to obtain FPT algorithms for a range of hard problems. Here we investigate what happens when a graph contains a modulator which is large but "well-structured" (in the sense of having bounded rank-width). Can such modulators still be exploited to obtain efficient algorithms? And is it even possible to find such modulators efficiently? #R##N#We first show that the parameters derived from such well-structured modulators are strictly more general than the cardinality of modulators and rank-width itself. Then, we develop an FPT algorithm for finding such well-structured modulators to any graph class which can be characterized by a finite set of forbidden induced subgraphs. We proceed by showing how well-structured modulators can be used to obtain efficient parameterized algorithms for Minimum Vertex Cover and Maximum Clique. Finally, we use well-structured modulators to develop an algorithmic meta-theorem for deciding problems expressible in Monadic Second Order (MSO) logic, and prove that this result is tight in the sense that it cannot be generalized to LinEMSO problems.

Includes members:
  Member "meta kernelization using well structured modulators":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "measuring what matters a hybrid approach to dynamic programming with treewidth")
  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 "chordal editing is fixed parameter tractable":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a polynomial kernel for 3 leaf power deletion")
  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 "meta kernelization with structural parameters":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "measuring what matters a hybrid approach to dynamic programming with treewidth")
  Member "backdoors to satisfaction":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "hunting for tractable languages for judgment aggregation")
  Member "practical and efficient split decomposition via graph labelled trees":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "circle graph isomorphism in almost linear time")
  Member "kernel bounds for path and cycle problems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "parameterized pre coloring extension and list coloring problems")

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)