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: "empirical coordination with channel feedback and strictly causal or causal encoding"
  Abstract: In multi-terminal networks, feedback increases the capacity region and helps communication devices to coordinate. In this article, we deepen the relationship between coordination and feedback by considering a point-to-point scenario with an information source and a noisy channel. Empirical coordination is achievable if the encoder and the decoder can implement sequences of symbols that are jointly typical for a target probability distribution. We investigate the impact of feedback when the encoder has strictly causal or causal observation of the source symbols. For both cases, we characterize the optimal information constraints and we show that feedback improves coordination possibilities. Surprisingly, feedback also reduces the number of auxiliary random variables and simplifies the information constraints. For empirical coordination with strictly causal encoding and feedback, the information constraint does not involve auxiliary random variable anymore.

Connected through hyperedge HE-1 (induced by source paper "coordination through shared randomness"):
  with members:
    - "communication for generating correlation a survey"
    - "on the optimality of secret key agreement via omniscience"
    - "polar coding for empirical coordination of signals and actions over noisy channels"
    - "on the public communication needed to achieve sk capacity in the multiterminal source model"
    - "secure cascade channel synthesis"
    - "on non interactive simulation of joint distributions"
    - "empirical coordination with two sided state information and correlated source and state"
    - "exact common information"

Connected through hyperedge HE-2 (induced by source paper "empirical coordination subject to a fidelity criterion"):
  with members:
    - "strong coordination of signals and actions over noisy channels"
    - "information design for strategic coordination of autonomous devices with non aligned utilities"
    - "coordination in distributed networks via coded actions with application to power control"
    - "empirical coordination with two sided state information and correlated source and state"
    - "empirical coordination in a triangular multiterminal network"

Connected through hyperedge HE-3 (induced by source paper "state leakage and coordination of actions core of the receiver s knowledge"):
  with members:
    - "information theoretic approach to strategic communication as a hierarchical game"
    - "coordination in distributed networks via coded actions with application to power control"
    - "correlation between channel state and information source with empirical coordination constraint"
    - "rate distortion theory for secrecy systems"
    - "causal state communication"
    - "hybrid codes needed for coordination over the point to point channel"
    - "coordination using implicit communication"

Connected through hyperedge HE-4 (induced by source paper "information design for strategic coordination of autonomous devices with non aligned utilities"):
  with members:
    - "on the role of side information in strategic communication"
    - "empirical and strong coordination via soft covering with polar codes"
    - "polar coding for empirical coordination of signals and actions over noisy channels"
    - "coordination in distributed networks via coded actions with application to power control"
    - "empirical coordination with two sided state information and correlated source and state"
    - "correlation between channel state and information source with empirical coordination constraint"
    - "rate distortion theory for secrecy systems"
    - "hybrid codes needed for coordination over the point to point channel"

Connected through hyperedge HE-5 (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"
    - "joint empirical coordination of source and channel"
    - "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-6 (induced by source paper "joint empirical coordination of source and channel"):
  with members:
    - "strong coordination of signals and actions over noisy channels"
    - "information design for strategic coordination of autonomous devices with non aligned utilities"
    - "polar coding for empirical coordination of signals and actions over noisy channels"
    - "coordination in distributed networks via coded actions with application to power control"
    - "secure cascade channel synthesis"
    - "strong coordination over multi hop line networks"
    - "zero error coordination"
    - "empirical coordination with two sided state information and correlated source and state"

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)