human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "matchings under preferences strength of stability and trade offs"
  Abstract: We propose two solution concepts for matchings under preferences: robustness and near stability. The former strengthens while the latter relaxes the classic definition of stability by Gale and Shapley (1962). Informally speaking, robustness requires that a matching must be stable in the classic sense, even if the agents slightly change their preferences. Near stability, on the other hand, imposes that a matching must become stable (again, in the classic sense) provided the agents are willing to adjust their preferences a bit. Both of our concepts are quantitative; together they provide means for a fine-grained analysis of stability for matchings. Moreover, our concepts allow to explore the trade-offs between stability and other criteria of societal optimality, such as the egalitarian cost and the number of unmatched agents. We investigate the computational complexity of finding matchings that implement certain predefined trade-offs. We provide a polynomial-time algorithm that given agents' preferences returns a socially optimal robust matching, and we prove that finding a socially optimal and nearly stable matching is computationally hard.

Connected through hyperedge HE-1 (induced by source paper "adapting stable matchings to evolving preferences"):
  with members:
    - "stable roommates with narcissistic single peaked and single crossing preferences"
    - "stable matchings robust solutions and distributive lattices"
    - "stable marriage with multi modal preferences"
    - "reoptimization of parameterized problems"
    - "parameterized dynamic cluster editing"
    - "finding stable matchings that are robust to errors in the input"
    - "finding robust solutions to stable marriage"
    - "how hard is it to satisfy almost all roommates"

Connected through hyperedge HE-2 (induced by source paper "stable roommates with narcissistic single peaked and single crossing preferences"):
  with members:
    - "stable marriage with multi modal preferences"
    - "stable marriage with groups of similar agents"
    - "how hard is it to satisfy almost all roommates"
    - "balanced stable marriage how close is close enough"
    - "stable marriage with covering constraints a complete computational trichotomy"
    - "modeling single peakedness for votes with ties"
    - "single peaked consistency for weak orders is easy"
    - "clone structures in voters preferences"

Connected through hyperedge HE-3 (induced by source paper "computational complexity of stable marriage and stable roommates and their variants"):
  with members:
    - "stable roommates with narcissistic single peaked and single crossing preferences"
    - "stable marriage with multi modal preferences"
    - "popular matchings and limits to tractability"
    - "on treewidth and stable marriage"
    - "how hard is it to satisfy almost all roommates"
    - "balanced stable marriage how close is close enough"
    - "the stable roommates problem with short lists"
    - "acyclic preference systems in p2p networks"

Question: Please tell me which class the center node 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.GT(Computer Science and Game Theory)