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: "popular matchings with multiple partners"
  Abstract: Our input is a bipartite graph $G = (R \cup H,E)$ where each vertex in $R \cup H$ has a preference list strictly ranking its neighbors. The vertices in $R$ (similarly, in $H$) are called residents (resp., hospitals): each resident seeks to be matched to a hospital while each hospital $h$ seeks $\mathsf{cap}(h) \ge 1$ many residents to be matched to it. The Gale-Shapley algorithm computes a stable matching in $G$ in linear time. We consider the problem of computing a popular matching in $G$ - a matching $M$ is popular if $M$ cannot lose an election to any other matching where vertices cast votes for one matching versus another. Our main contribution is to show that a max-size popular matching in $G$ can be computed by the 2-level Gale-Shapley algorithm in linear time. This is a simple extension of the classical Gale-Shapley algorithm and we prove its correctness via linear programming.

Connected through hyperedge HE-1 (induced by source paper "how good are popular matchings"):
  with members:
    - "envy free matchings with lower quotas"
    - "popular matching with lower quotas"
    - "popularity in the generalized hospital residents setting"
    - "almost stable matchings in the hospitals residents problem with couples"
    - "popular edges and dominant matchings"

Connected through hyperedge HE-2 (induced by source paper "max size popular matchings and extensions"):
  with members:
    - "popular matchings with two sided preferences and one sided ties"
    - "popular edges and dominant matchings"

Connected through hyperedge HE-3 (induced by source paper "popularity in the generalized hospital residents setting"):
  with members:
    - "popular edges and dominant matchings"
    - "classified stable matching"

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)