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 "fixed error asymptotics for erasure and list decoding"):
  Abstract: We derive the optimum second-order coding rates, known as second-order capacities, for erasure and list decoding. For erasure decoding for discrete memoryless channels, we show that second-order capacity is $\sqrt{V}\Phi^{-1}(\epsilon_t)$ where $V$ is the channel dispersion and $\epsilon_t$ is the total error probability, i.e., the sum of the erasure and undetected errors. We show numerically that the expected rate at finite blocklength for erasures decoding can exceed the finite blocklength channel coding rate. We also show that the analogous result also holds for lossless source coding with decoder side information, i.e., Slepian-Wolf coding. For list decoding, we consider list codes of deterministic size that scales as $\exp(\sqrt{n}l)$ and show that the second-order capacity is $l+\sqrt{V}\Phi^{-1}(\epsilon)$ where $\epsilon$ is the permissible error probability. We also consider lists of polynomial size $n^\alpha$ and derive bounds on the third-order coding rate in terms of the order of the polynomial $\alpha$. These bounds are tight for symmetric and singular channels. The direct parts of the coding theorems leverage on the simple threshold decoder and converses are proved using variants of the hypothesis testing converse.

Includes members:
  Member "the third order term in the normal approximation for the awgn channel":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "gaussian multiple and random access in the finite blocklength regime")
  Member "list decoding random coding exponents and expurgated exponents":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "mismatched guesswork")
  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 "a tight upper bound for the third order asymptotics for most discrete memoryless channels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "finite sample analysis of image registration")
  Member "feedback communication systems with limitations on incremental redundancy":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "optimizing transmission lengths for limited feedback with non binary ldpc examples")
  Member "erasure list exponents for slepian wolf decoding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "gaussian intersymbol interference channels with mismatch")
  Member "reliability based error detection for feedback communication with low latency":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "asymptotic estimates in information theory with non vanishing error probabilities")
  Member "the third order term in the normal approximation for singular channels":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "asymptotic estimates in information theory with non vanishing error probabilities")

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)