human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "coordination through shared randomness"):
  Abstract: We study a distributed sampling problem where a set of processors want to output approximately (in the sense of asymptotically vanishing total variation distance) independent and identically distributed samples from a given joint distribution with the help of a coordinator. We consider two settings. In the omniscient coordinator setting, the coordinator has access to several independent sources of randomness and each processor has access to a subset of these sources. The oblivious coordinator setting is similar except that the coordinator does not have access to any of the shared randomness sources. In addition, all processors and the coordinator may privately randomize. In the omniscient coordinator setting, when the subsets at the processors are disjoint (individually shared randomness model), we characterize the rate of communication required from the coordinator to the processors over a multicast link. We also give an upper bound on the communication rate for the randomness-on-the-forehead model where each processor observes all but one source of randomness and we give an achievable strategy in the omniscient coordinator setting for the general case where the processors have access to arbitrary subsets of sources of randomness. Also, we consider a more general model where the processors observe components of correlated sources (with the coordinator observing all the components), where we characterize the communication rate when all the processors wish to output the same random sequence. In the oblivious coordinator setting, we completely characterize the trade-off region between the communication and shared randomness rates for the general case where the processors have access to arbitrary subsets of sources of randomness.

Includes members:
  Member "communication for generating correlation a survey":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "strong converse using change of measure arguments")
  Member "on the optimality of secret key agreement via omniscience":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "secret key agreement for hypergraphical sources with limited total discussion")
  Member "polar coding for empirical coordination of signals and actions over noisy channels":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "strong coordination of signals and actions over noisy channels with two sided state information")
  Member "on the public communication needed to achieve sk capacity in the multiterminal source model":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "communication for generating correlation a unifying survey")
  Member "secure cascade channel synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "distributed source simulation with no communication")
  Member "on non interactive simulation of joint distributions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "communication for generating correlation a unifying survey")
  Member "empirical coordination with two sided state information and correlated source and state":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "strategic communication with side information at the decoder")
  Member "empirical coordination with channel feedback and strictly causal or causal encoding":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "empirical coordination subject to a fidelity criterion")

Question: Please tell me which class the source paper 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)