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: "game theoretic aspects of distributed spectral coordination with application to dsl networks"
  Abstract: In this paper we use game theoretic techniques to study the value of cooperation in distributed spectrum management problems. We show that the celebrated iterative water-filling algorithm is subject to the prisoner’s dilemma and therefore can lead to severe degradation of the achievable rate region in an interference channel environment. We also provide thorough analysis of a simple two bands near-far situation where we are able to provide closed form tight bounds on the rate region of both fix ed margin iterative water filling (FM-IWF) and dynamic frequency division multiplexing (DFDM) methods. This is the only case where such analytic expressions are known and all previous studies included only simulated results of the rate region. We then propose an alternative algorithm that alleviates some of the drawbacks of the IWF algorithm in near-far scenarios relevant to DSL access networks. We also provide experimental analysis based on measured DSL channels of both algorithms as well as the centralized optimum spectrum management.

Connected through hyperedge HE-1 (induced by source paper "channel equilibrium networks for learning deep representation"):
  with members:
    - "grad cam visual explanations from deep networks via gradient based localization"
    - "switchable whitening for deep representation learning"
    - "gcnet non local networks meet squeeze excitation networks and beyond"
    - "mmdetection open mmlab detection toolbox and benchmark"
    - "iterative normalization beyond standardization towards efficient whitening"
    - "mobilenetv2 inverted residuals and linear bottlenecks"
    - "shufflenet v2 practical guidelines for efficient cnn architecture design"
    - "the lottery ticket hypothesis finding sparse trainable neural networks"

Connected through hyperedge HE-2 (induced by source paper "competitive spectrum management with incomplete information"):
  with members:
    - "game theory and the frequency selective interference channel"
    - "distributed power allocation with rate constraints in gaussian parallel interference channels"
    - "competition in wireless systems via bayesian interference games"
    - "cooperative game theory and the gaussian interference channel"

Connected through hyperedge HE-3 (induced by source paper "game theory and the frequency selective interference channel"):
  with members:
    - "distributed power allocation with rate constraints in gaussian parallel interference channels"
    - "energy efficient resource allocation in wireless networks"
    - "cooperative game theory and the gaussian interference channel"
    - "bargaining over the interference channel"

Connected through hyperedge HE-4 (induced by source paper "interference avoidance game in the gaussian interference channel sub optimal and optimal schemes"):
  with members:
    - "a new perspective on multi user power control games in interference channels"
    - "a distributed dynamic frequency allocation algorithm"

Connected through hyperedge HE-5 (induced by source paper "cooperative game theory and the gaussian interference channel"):
  with members:
    - "bargaining over the interference channel"

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.IT(Information Theory)