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 "an efficient algorithm for enumerating all possible input nodes in controlling complex networks"):
  Abstract: Controlling complex networks is of great importance in many application regions. Recent works found that the minimum number of input nodes (MIS) used to control a network can be obtained by the maximum matching. However, the maximum matchings of a network are not unique, and there may exist numerous MISs. Finding all possible input nodes is difficult for the large-scale networks because of high computational costs. Here we present an efficient algorithm to enumerating all possible input nodes of a network. We rigorously prove that all possible input nodes can be obtained by a simple modification of the maximum matching algorithm, which allows us to obtain all possible input nodes (the union of all MISs) by only computing one MIS. The experiment results on both synthetic and real networks show that the computational complexity of the proposed algorithm is significantly improved contrast to the previous one. Speedup of up 100000x compared with the previous algorithm was observed for large-scale synthetic networks and real networks.

Includes members:
  Member "input graph the hidden geometry in controlling complex networks":
    also connected through other hyperedges:
      (none)
  Member "community structure in large networks natural cluster sizes and the absence of large well defined clusters":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "certified robustness of community detection against adversarial structural perturbation via randomized smoothing")
  Member "mapping the gnutella network properties of large scale peer to peer systems and implications for system design":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "network interdiction using adversarial traffic flows")

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)