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 "error exponent bounds for the bee identification problem"):
  Abstract: Consider the problem of identifying a massive number of bees, uniquely labeled with barcodes, using noisy measurements. We formally introduce this `bee-identification problem', define its error exponent, and derive efficiently computable upper and lower bounds for this exponent. We show that joint decoding of barcodes provides a significantly better exponent compared to separate decoding followed by permutation inference. For low rates, we prove that the lower bound on the bee-identification exponent obtained using typical random codes (TRC) is strictly better than the corresponding bound obtained using a random code ensemble (RCE). Further, as the rate approaches zero, we prove that the upper bound on the bee-identification exponent meets the lower bound obtained using TRC with joint barcode decoding.

Includes members:
  Member "capacity results for the noisy shuffling channel":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dna based storage models and fundamental limits")
  Member "the strongly asynchronous massive access channel":
    also connected through other hyperedges:
      (none)
  Member "on identifying a massive number of distributions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the bee identification error exponent with absentee bees")
  Member "codes in the space of multisets coding for permutation channels with impairments":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimal constant weight codes under l_1 metric")
  Member "fundamental limits of dna storage systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "dna based storage models and fundamental limits")
  Member "error exponents of typical random codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "large deviations behavior of the logarithmic error probability of random codes")

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)