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: "cooperative game theory and the gaussian interference channel"
  Abstract: In this paper we discuss the use of cooperative game theory for analyzing interference channels. We extend our previous work, to games with N players as well as frequency selective channels and joint TDM/FDM strategies. #R##N#We show that the Nash bargaining solution can be computed using convex optimization techniques. We also show that the same results are applicable to interference channels where only statistical knowledge of the channel is available. Moreover, for the special case of two players $2\times K$ frequency selective channel (with K frequency bins) we provide an $O(K \log_2 K)$ complexity algorithm for computing the Nash bargaining solution under mask constraint and using joint FDM/TDM strategies. Simulation results are also provided.

Connected through hyperedge HE-1 (induced by source paper "distributed learning for channel allocation over a shared spectrum"):
  with members:
    - "deep reinforcement learning for dynamic multichannel access in wireless networks"
    - "game of thrones fully distributed learning for multi player bandits"
    - "proactive resource management for lte in unlicensed spectrum a deep learning perspective"
    - "deep multi user reinforcement learning for distributed dynamic spectrum access"
    - "game theoretic dynamic channel allocation for frequency selective interference channels"
    - "proactive resource management in lte u systems a deep learning perspective"
    - "propagation path loss models for 5g urban micro and macro cellular scenarios"
    - "multi player bandits a musical chairs approach"

Connected through hyperedge HE-2 (induced by source paper "approximate best response dynamics in random interference games"):
  with members:
    - "asymptotically optimal distributed channel allocation a competitive game theoretic approach"
    - "distributed learning algorithms for spectrum sharing in spatial random access wireless networks"
    - "dynamics in near potential games"
    - "on the structure of weakly acyclic games"
    - "game theory and the frequency selective interference channel"
    - "on the complexity of nash dynamics and sink equilibria"

Connected through hyperedge HE-3 (induced by source paper "secret key generation in many to one networks an integrated game theoretic and information theoretic approach"):
  with members:
    - "polar coding for the broadcast channel with confidential messages a random binning analogy"
    - "the capacity region of the source type model for secret key and private key generation"
    - "polar coding for secret key generation"
    - "separation of reliability and secrecy in rate limited secret key generation"
    - "a game theoretic view of the interference channel impact of coordination and bargaining"
    - "a constrained evolutionary gaussian multiple access channel game"
    - "secret key and private key constructions for simple multiterminal source models"
    - "shannon meets nash on the interference channel"

Connected through hyperedge HE-4 (induced by source paper "game theoretic dynamic channel allocation for frequency selective interference channels"):
  with members:
    - "approximate best response dynamics in random interference games"
    - "asymptotically optimal distributed channel allocation a competitive game theoretic approach"
    - "fully distributed optimal channel assignment for open spectrum access"
    - "on the nash equilibria in decentralized parallel interference channels"
    - "learning equilibria with partial information in decentralized wireless networks"
    - "shannon meets nash on the interference channel"
    - "game theory and the frequency selective interference channel"
    - "the mimo iterative waterfilling algorithm"

Connected through hyperedge HE-5 (induced by source paper "distributed learning algorithms for spectrum sharing in spatial random access wireless networks"):
  with members:
    - "fast responsive decentralised graph colouring"
    - "learning based constraint satisfaction with sensing restrictions"
    - "distributed game theoretic optimization and management of multichannel aloha networks"
    - "distributed spectrum access with spatial reuse"
    - "bargaining over the interference channel"

Connected through hyperedge HE-6 (induced by source paper "asymptotically optimal distributed channel allocation a competitive game theoretic approach"):
  with members:
    - "fully distributed optimal channel assignment for open spectrum access"
    - "competitive design of multiuser mimo systems based on game theory a unified view"
    - "adaptive channel allocation spectrum etiquette for cognitive radio networks"

Connected through hyperedge HE-7 (induced by source paper "on the capacity and degrees of freedom regions of two user mimo interference channels with limited receiver cooperation"):
  with members:
    - "leveraging physical layer capabilites distributed scheduling in interference networks with local views"
    - "a survey on device to device communication in cellular networks"
    - "on the capacity region and the generalized degrees of freedom region for the mimo interference channel with feedback"
    - "fundamental limits of cooperation"
    - "the capacity region of the mimo interference channel and its reciprocity to within a constant gap"
    - "on achieving local view capacity via maximal independent graph scheduling"
    - "multi user mimo with outdated csi training feedback and scheduling"
    - "interference channels with source cooperation"

Connected through hyperedge HE-8 (induced by source paper "on the allocation of multiple divisible assets to players with different utilities"):
  with members:
    - "weighted max min resource allocation for frequency selective channels"
    - "game theory and the frequency selective interference channel"
    - "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)