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 "a lagrange dual lower bound to the error exponent function of the typical random code"):
  Abstract: A Lagrange-dual (Gallager-style) lower bound is derived for the error exponent function of the typical random code (TRC) pertaining to the i.i.d. random coding ensemble and mismatched stochastic likelihood decoding. While the original expression, derived from the method of types (the Csiszar-style expression) involves minimization over probability distributions defined on the channel input--output alphabets, the new Lagrange-dual formula involves optimization of five parameters, independently of the alphabet sizes. For both stochastic and deterministic mismatched decoding (including maximum likelihood decoding as a special case),we provide a rather comprehensive discussion on the insight behind the various ingredients of this formula and describe how its behavior varies as the coding rate exhausts the relevant range. Among other things, it is demonstrated that this expression simultaneously generalizes both the expurgated error exponent function (at zero rate) and the classical random coding exponent function at high rates, where it also meets the sphere--packing bound.

Includes members:
  Member "error exponents of typical random trellis codes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "large deviations behavior of the logarithmic error probability of random codes")
  Member "error exponents of typical random codes for the colored gaussian channel":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "large deviations behavior of the logarithmic error probability of random codes")
  Member "error exponents of typical random codes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "large deviations behavior of the logarithmic error probability of random codes")
  Member "correction to the generalized stochastic likelihood decoder random coding and expurgated bounds":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "ensemble performance of biometric authentication systems based on secret key generation")
  Member "the likelihood encoder for lossy compression":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "keyless covert communication via channel state information")
  Member "the generalized stochastic likelihood decoder random coding and expurgated bounds":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sharp bounds for mutual covering")
  Member "a technique for deriving one shot achievability results in network information theory":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "exponential strong converse for successive refinement with causal decoder side information")

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)