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: "joint empirical coordination of source and channel"
  Abstract: In a decentralized and self-configuring network, the communication devices are considered as autonomous decision-makers that sense their environment and that implement optimal transmission schemes. It is essential that these autonomous devices cooperate and coordinate their actions, to ensure the reliability of the transmissions and the stability of the network. We study a point-to-point scenario in which the encoder and the decoder implement decentralized policies that are coordinated. The coordination is measured in terms of empirical frequency of symbols of source and channel. The encoder and the decoder perform a coding scheme such that the empirical distribution of the symbols is close to a target joint probability distribution. We characterize the set of achievable target probability distributions for a point-to-point source-channel model, in which the encoder is non-causal and the decoder is strictly causal i.e., it returns an action based on the observation of the past channel outputs. The objectives of the encoder and of the decoder, are captured by some utility function, evaluated with respect to the set of achievable target probability distributions. In this article, we investigate the maximization problem of a utility function that is common to both encoder and decoder. We show that the compression and the transmission of information are particular cases of the empirical coordination.

Connected through hyperedge HE-1 (induced by source paper "strategic communication with side information at the decoder"):
  with members:
    - "strong coordination of signals and actions over noisy channels with two sided state information"
    - "persuasion with limited communication capacity"
    - "information design for strategic coordination of autonomous devices with non aligned utilities"
    - "information theoretic approach to strategic communication as a hierarchical game"
    - "on the role of side information in strategic communication"
    - "persuasion with limited communication"
    - "algorithmic bayesian persuasion"
    - "empirical coordination with two sided state information and correlated source and state"

Connected through hyperedge HE-2 (induced by source paper "persuasion with limited communication capacity"):
  with members:
    - "information design for strategic coordination of autonomous devices with non aligned utilities"
    - "information theoretic approach to strategic communication as a hierarchical game"
    - "nash codes for noisy channels"
    - "coordination using implicit communication"

Connected through hyperedge HE-3 (induced by source paper "empirical and strong coordination via soft covering with polar codes"):
  with members:
    - "secure multiplex coding with dependent and non uniform multiple messages"
    - "f divergence inequalities"
    - "covert communication over noisy channels a resolvability perspective"
    - "coordination in distributed networks via coded actions with application to power control"
    - "bounds among f divergences"
    - "semantic security capacity for wiretap channels of type ii"
    - "strong coordination over multi hop line networks"
    - "empirical coordination for joint source channel coding"

Connected through hyperedge HE-4 (induced by source paper "empirical coordination with two sided state information and correlated source and state"):
  with members:
    - "coordination in distributed networks via coded actions with application to power control"
    - "empirical coordination with channel feedback and strictly causal or causal encoding"
    - "coded power control performance analysis"
    - "correlation between channel state and information source with empirical coordination constraint"
    - "causal state communication"
    - "strong coordination with polar codes"
    - "hybrid codes needed for coordination over the point to point channel"
    - "coordination using implicit communication"

Connected through hyperedge HE-5 (induced by source paper "coordination in state dependent distributed networks the two agent case"):
  with members:
    - "coordination in distributed networks via coded actions with application to power control"
    - "empirical coordination for joint source channel coding"
    - "coded power control performance analysis"
    - "causal state communication"
    - "coordination using implicit communication"

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)