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 "the third order term in the normal approximation for the awgn channel"):
  Abstract: This paper shows that, under the average error probability formalism, the third-order term in the normal approximation for the additive white Gaussian noise channel with a maximal or equal power constraint is at least    $({1}/{2})\log n\,+\,O(1)$   . This improves on the lower bound by Polyanskiys–Poor–Verdu (2010) and matches the upper bound proved by the same authors.

Includes members:
  Member "second order asymptotics for the gaussian mac with degraded message sets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "second order region for gray wyner network")
  Member "a tight upper bound for the third order asymptotics for most discrete memoryless channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "finite sample analysis of image registration")
  Member "mismatched decoding error exponents second order rates and saddlepoint approximations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "saddlepoint approximations for short packet wireless communications")
  Member "refinement of the random coding bound":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "second order asymptotics of sequential hypothesis testing")
  Member "a derivation of the asymptotic random coding prefactor":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on exact asymptotics of the error probability in channel coding symmetric channels")
  Member "the third order term in the normal approximation for singular channels":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "asymptotic estimates in information theory with non vanishing error probabilities")
  Member "the log volume of optimal codes for memoryless channels asymptotically within a few nats":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "finite sample analysis of image registration")
  Member "a finite blocklength perspective on gaussian multi access channels":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a proof of the strong converse theorem for gaussian multiple access channels")

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)