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: "zero error coordination"
  Abstract: In this paper, we consider a zero error coordination problem wherein the nodes of a network exchange messages to be able to perfectly coordinate their actions with the individual observations of each other. While previous works on coordination commonly assume an asymptotically vanishing error, we assume exact, zero error coordination. Furthermore, unlike previous works that employ the empirical or strong notions of coordination, we define and use a notion of set coordination. This notion of coordination bears similarities with the empirical notion of coordination. We observe that set coordination, in its special case of two nodes with a one-way communication link is equivalent with the "Hide and Seek" source coding problem of McEliece and Posner. The Hide and Seek problem has known intimate connections with graph entropy, rate distortion theory, Renyi mutual information and even error exponents. Other special cases of the set coordination problem relate to Witsenhausen's zero error rate and the distributed computation problem. These connections motivate a better understanding of set coordination, its connections with empirical coordination, and its study in more general setups. This paper takes a first step in this direction by proving new results for two node networks.

Connected through hyperedge HE-1 (induced by source paper "distributed source simulation with no communication"):
  with members:
    - "decidability of non interactive simulation of joint distributions"
    - "secure cascade channel synthesis"
    - "on non interactive simulation of joint distributions"
    - "a stronger soft covering lemma and applications"
    - "exact common information"
    - "analysis of boolean functions"
    - "simulation of a channel with another channel"
    - "distributed channel synthesis"

Connected through hyperedge HE-2 (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"
    - "empirical coordination with two sided state information and correlated source and state"
    - "empirical coordination with channel feedback and strictly causal or causal encoding"

Connected through hyperedge HE-3 (induced by source paper "empirical coordination for joint source channel coding"):
  with members:
    - "coordination in distributed networks via coded actions with application to power control"
    - "secure cascade channel synthesis"
    - "strong coordination over multi hop line networks"
    - "coordination in state dependent distributed networks the two agent case"
    - "coded power control performance analysis"
    - "correlation between channel state and information source with empirical coordination constraint"
    - "strong coordination over a line network"
    - "empirical processes typical sequences and coordinated actions in standard borel spaces"

Connected through hyperedge HE-4 (induced by source paper "simulation of a channel with another channel"):
  with members:
    - "exact common information"
    - "renyi divergence and kullback leibler divergence"
    - "distributed channel synthesis"
    - "achievability proof via output statistics of random binning"
    - "channel simulation via interactive communications"
    - "hybrid codes needed for coordination over the point to point channel"
    - "a new data processing inequality and its applications in distributed source and channel coding"
    - "on extracting common random bits from correlated sources"

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)