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: "facility location with double peaked preference"
  Abstract: We study the problem of locating a single facility on a real line based on the reports of self-interested agents, when agents have double-peaked preferences, with the peaks being on opposite sides of their locations. We observe that double-peaked preferences capture real-life scenarios and thus complement the well-studied notion of single-peaked preferences. We mainly focus on the case where peaks are equidistant from the agents' locations and discuss how our results extend to more general settings. We show that most of the results for single-peaked preferences do not directly apply to this setting; this makes the problem essentially more challenging. As our main contribution, we present a simple truthful-in-expectation mechanism that achieves an approximation ratio of 1+b/c for both the social and the maximum cost, where b is the distance of the agent from the peak and c is the minimum cost of an agent. For the latter case, we provide a 3/2 lower bound on the approximation ratio of any truthful-in-expectation mechanism. We also study deterministic mechanisms under some natural conditions, proving lower bounds and approximation guarantees. We prove that among a large class of reasonable mechanisms, there is no deterministic mechanism that outperforms our truthful-in-expectation mechanism.

Connected through hyperedge HE-1 (induced by source paper "average case analysis of the assignment problem with independent preferences"):
  with members:
    - "smoothed and average case approximation ratios of mechanisms beyond the worst case analysis"
    - "average case approximation ratio of scheduling without payments"
    - "social welfare in one sided matching mechanisms"
    - "an axiomatic approach to characterizing and relaxing strategyproofness of one sided matching mechanisms"
    - "social welfare in one sided matchings random priority and beyond"
    - "the computational complexity of random serial dictatorship"
    - "social welfare in one sided matching markets without money"
    - "truthful assignment without money"

Connected through hyperedge HE-2 (induced by source paper "the control complexity of r approval from the single peaked case to the general case"):
  with members:
    - "computational aspects of nearly single peaked electorates"
    - "are there any nicely structured preference profiles nearby"
    - "election attacks with few candidates"
    - "kernelization complexity of possible winner and coalitional manipulation problems in voting"
    - "computational aspects of multi winner approval voting"
    - "the complexity of fully proportional representation for single crossing electorates"
    - "the complexity of manipulative attacks in nearly single peaked electorates"
    - "the complexity of manipulating k approval elections"

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)