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: "possible winners in noisy elections"
  Abstract: We consider the problem of predicting winners in elections, for the case where we are given complete knowledge about all possible candidates, all possible voters (together with their preferences), but where it is uncertain either which candidates exactly register for the election or which voters cast their votes. Under reasonable assumptions, our problems reduce to counting variants of election control problems. We either give polynomial-time algorithms or prove #P-completeness results for counting variants of control by adding/deleting candidates/voters for Plurality, k-Approval, Approval, Condorcet, and Maximin voting rules. We consider both the general case, where voters' preferences are unrestricted, and the case where voters' preferences are single-peaked.

Connected through hyperedge HE-1 (induced by source paper "election with bribed voter uncertainty hardness and approximation algorithm"):
  with members:
    - "when the cookie meets the blockchain privacy risks of web payments via cryptocurrencies"
    - "complexity of manipulation bribery and campaign management in bucklin and fallback voting"
    - "determining possible and necessary winners under common voting rules given partial orders"
    - "taking the final step to a full dichotomy of the possible winner problem in pure scoring rules"
    - "multimode control attacks on elections"
    - "the complexity of manipulating k approval elections"
    - "towards a dichotomy for the possible winner problem in elections based on scoring rules"
    - "how hard is bribery in elections"

Connected through hyperedge HE-2 (induced by source paper "weighted electoral control"):
  with members:
    - "a control dichotomy for pure scoring rules"
    - "control in the presence of manipulators cooperative and competitive cases"
    - "schulze and ranked pairs voting are fixed parameter tractable to bribe manipulate and control"
    - "how many vote operations are needed to manipulate a voting system"
    - "control complexity in bucklin fallback and plurality voting an experimental approach"
    - "an atypical survey of typical case heuristic algorithms"
    - "new candidates welcome possible winners with respect to the addition of new candidates"
    - "the complexity of manipulative attacks in nearly single peaked electorates"

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)