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: "a parametric worst case approach to fairness in tu cooperative games"
  Abstract: We propose a parametric family of measures of fairness in allocations of TU-cooperative games. Their definition is based on generalized Renyi Entropy, is related to the Cowell-Kuga generalized entropy indices in welfare economics, and aims to parallel the spirit of the notion of price of anarchy in the case of convex TU-cooperative games. #R##N#Since computing these indices is NP-complete in general, we first upper bound the performance of a "reverse greedy" algorithm for approximately computing worst-case fairness. The result provides a general additive error guarantee in terms of two (problem dependent) packing constants. We then particularize this result to the class of induced subset games. For such games computing worst-case fairness is NP-complete, and the additive guarantee constant can be explicitly computed. We compare this result to the performance of an alternate algorithm based on "biased orientations".

Connected through hyperedge HE-1 (induced by source paper "minimum entropy submodular optimization and fairness in cooperative games"):
  with members:
    - "minimum entropy combinatorial optimization problems"
    - "partition reduction for lossy data compression problem"
    - "interactive submodular set cover"
    - "adaptive submodularity theory and applications in active learning and stochastic optimization"
    - "minimum entropy orientations"
    - "information inequalities for joint distributions with interpretations and applications"

Connected through hyperedge HE-2 (induced by source paper "improved approximation algorithms for low density instances of the minimum entropy set cover problem"):
  with members:
    - "minimum entropy submodular optimization and fairness in cooperative games"
    - "minimum entropy combinatorial optimization problems"
    - "set covering problems with general objective functions"
    - "minimum entropy orientations"

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)