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 "local large deviations a mcmillian theorem for typed random graph processes"):
  Abstract: For a finite typed graph on n nodes and with type law µ on finite alphabet Γ, we define the spectral potential ρλ(., µ), of the graph. From the ρλ(., µ) we define the Kullback action or the divergence function, Hλ(π || v), with respect to an empirical link measure, π, as the Legendre dual. For the finite typed random graph conditioned to have an empirical link measure π and empirical type measure µ, we prove a Local large Deviation Principle (LLDP), with rate function Hλ(π || v) and speed n. From this LLDP, we obtain a full conditional large deviation principle and a weak variant of the classical McMillian Theorem for the typed random graph models. Given the typical empirical link measure, λµ⊗µ, we show that, the number of typed random graphs is equal to en||λµ⊗µ||H(λµ⊗µ⁄||λµ⊗µ||) approximately. Note that we do not require any topological restrictions on the space of finite graphs for these LLDPs.

Includes members:
  Member "lossy asymptotic equipartition property for networked data structures":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "lossy asymptotic equipartition property for geometric networked data structures")
  Member "lossy asymptotic equipartition property for hierarchical data structures":
    also connected through other hyperedges:
      (none)
  Member "local large deviations mcmillian theorem for multitype galton watson processes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "local large deviation principle large deviation principle and information theory for the signal to interference and noise ratio graph models")

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)