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 "wyner s common information under r enyi divergence measures"):
  Abstract: We study a generalized version of Wyner's common information problem (also coined the distributed sources simulation problem). The original common information problem consists in understanding the minimum rate of the common input to independent processors to generate an approximation of a joint distribution when the distance measure used to quantify the discrepancy between the synthesized and target distributions is the normalized relative entropy. Our generalization involves changing the distance measure to the unnormalized and normalized Renyi divergences of order $\alpha=1+s\in[0,2]$. We show that the minimum rate needed to ensure the Renyi divergences between the distribution induced by a code and the target distribution vanishes remains the same as the one in Wyner's setting, except when the order $\alpha=1+s=0$. This implies that Wyner's common information is rather robust to the choice of distance measure employed. As a by product of the proofs used to the establish the above results, the exponential strong converse for the common information problem under the total variation distance measure is established.

Includes members:
  Member "second order region for gray wyner network":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the dispersion of the gauss markov source")
  Member "exact random coding secrecy exponents for the wiretap channel":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "communication for generating correlation a unifying survey")
  Member "discrete lossy gray wyner revisited second order asymptotics large and moderate deviations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "exponential strong converse for successive refinement with causal decoder side information")
  Member "analysis of remaining uncertainties and exponents under various conditional r e nyi entropies":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the renyi capacity and center")
  Member "exponent function for source coding with side information at the decoder at rates below the rate distortion function":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a new proof of nonsignalling multiprover parallel repetition theorem")
  Member "on the renyi divergence joint range of relative entropies and a channel coding theorem":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the renyi capacity and center")
  Member "exact common information":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "communication for generating correlation a unifying survey")
  Member "renyi divergence and kullback leibler divergence":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "review analyze and design a comprehensive deep reinforcement learning framework")

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)