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 "second order asymptotics for the gaussian mac with degraded message sets"):
  Abstract: This paper studies the second-order asymptotics of the Gaussian multiple-access channel with degraded message sets. For a fixed average error probability    $ \varepsilon \in (0,1)$    and an arbitrary point on the boundary of the capacity region, we characterize the speed of convergence of rate pairs that converge to that boundary point for codes that have asymptotic error probability no larger than    $ \varepsilon $   . As a stepping stone to this local notion of the second-order asymptotics, we study a global notion, and establish relationships between the two. We provide a numerical example to illustrate how the angle of approach to a boundary point affects the second-order coding rate. This is the first conclusive characterization of the second-order asymptotics of a network information theory problem in which the capacity region is not a polygon.

Includes members:
  Member "asymptotic estimates in information theory with non vanishing error probabilities":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "finite sample analysis of image registration")
  Member "the third order term in the normal approximation for the awgn channel":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "gaussian multiple and random access in the finite blocklength regime")
  Member "on the dispersions of three network information theory problems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "gaussian multiple and random access in the finite blocklength regime")
  Member "second order asymptotics for the discrete memoryless mac with degraded message sets":
    also connected through other hyperedges:
      (none)
  Member "mismatched decoding error exponents second order rates and saddlepoint approximations":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "saddlepoint approximations for short packet wireless communications")
  Member "second order resolvability intrinsic randomness and fixed length source coding for mixed sources information spectrum approach":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "interval algorithm for random number generation information spectrum approach")
  Member "second order rate region of constant composition codes for the multiple access channel":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "gaussian multiple and random access in the finite blocklength regime")
  Member "non asymptotic and second order achievability bounds for coding with side information":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a case where interference does not affect the channel dispersion")

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)