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 "a quasi linear time b matching algorithm on distance hereditary graphs and bounded split width graphs"):
  Abstract: We present a quasi linear-time algorithm for Maximum Matching on distance-hereditary graphs and some of their generalizations. This improves on [Dragan, WG'97], who proposed such an algorithm for the subclass of (tent,hexahedron)-free distance-hereditary graphs. Furthermore, our result is derived from a more general one that is obtained for b-Matching. In the (unit cost) b-Matching problem, we are given a graph G = (V, E) together with a nonnegative integer capacity b v for every vertex v ∈ V. The objective is to assign nonnegative integer weights (x e) e∈E so that: for every v ∈ V the sum of the weights of its incident edges does not exceed b v , and e∈E x e is maximized. We present the first algorithm for solving b-Matching on cographs, distance-hereditary graphs and some of their generalizations in quasi linear time. For that, we use a decomposition algorithm that outputs for any graph G a collection of subgraphs of G with no edge-cutsets inducing a complete bipartite subgraph (a.k.a., splits). The latter collection is sometimes called a split decomposition of G. Furthermore, there exists a generic method in order to design graph algorithms based on split decomposition [Rao, DAM'08]. However, this technique only applies to " localized " problems: for which a " best " partial solution for any given subgraph in a split decomposition can be computed almost independently from the remaining of the graph. Such framework does not apply to matching problems since an augmenting path may cross the subgraphs arbitrarily. We introduce a new technique that somehow captures all the partial solutions for a given union of subgraphs in a split decomposition, in a compact and amenable way for algorithms — assuming some piecewise linear assumption holds on the value of such solutions. The latter assumption is shown to hold for b-Matching. Doing so, we prove that solving b-Matching on any pair G, b can be reduced in quasi linear-time to solving this problem on a collection of smaller graphs: that are obtained from the subgraphs in any split decomposition of G by replacing every vertex with a constant-size module. In particular, if G has a split decomposition where all subgraphs have order at most a fixed k, then we can solve b-Matching for G, b in O((k log 2 k)·(m+n)·log ||b|| 1)-time. This answers an open question of [Coudert et al., SODA'18].

Includes members:
  Member "parameterized aspects of triangle enumeration":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on adaptive algorithms for maximum matching")
  Member "fully polynomial fpt algorithms for some classes of bounded clique width graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "iterated type partitions")
  Member "the weighted matching approach to maximum cardinality matching":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a weighted approach to the maximum cardinality bipartite matching problem with applications in geometric settings")
  Member "on the power of tree depth for fully polynomial fpt algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on adaptive algorithms for maximum matching")
  Member "when can graph hyperbolicity be computed in linear time":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fast approximation and exact computation of negative curvature parameters of graphs")
  Member "a linear time algorithm for maximum cardinality matching on cocomparability graphs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on adaptive algorithms for maximum matching")
  Member "data structures for weighted matching and extensions to b matching and f factors":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a scaling algorithm for weighted f factors in general graphs")
  Member "fully polynomial time parameterized computations for graphs and matrices of low treewidth":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "minimum cuts in surface graphs")

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)