human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "a neyman pearson approach to universal erasure and list decoding"
  Abstract: We study communication over an unknown, possibly unreliable, discrete memoryless channel. For such problems, an erasure option at the decoder is desirable. We use constant-composition random codes and propose a generalization of the Maximum Mutual Information decoder. The proposed decoder is parameterized by a weighting function that can be designed to optimize the fundamental tradeoff between undetected-error and erasure exponents. Explicit solutions are identified. The class of functions can be further enlarged to optimize a similar tradeoff for list decoders. The optimal exponents admit simple expressions in terms of the sphere-packing exponent, at all rates below capacity. For small erasure exponents, these expressions coincide with those derived by Forney (1968) for symmetric channels, using Maximum a Posteriori decoding. Thus for those channels at least, ignorance of the channel law is inconsequential.

Connected through hyperedge HE-1 (induced by source paper "exact error and erasure exponents for the asymmetric broadcast channel"):
  with members:
    - "exact random coding exponents and universal decoders for the asymmetric broadcast channel"
    - "expurgated bounds for the asymmetric broadcast channel"
    - "random coding error exponents for the two user interference channel"
    - "simplified erasure list decoding"
    - "asymmetric evaluations of erasure and undetected error probabilities"
    - "exact random coding error exponents of optimal bin index decoding"
    - "erasure list random coding error exponents are not universally achievable"
    - "error exponents for broadcast channels with degraded message sets"

Connected through hyperedge HE-2 (induced by source paper "simplified erasure list decoding"):
  with members:
    - "asymmetric evaluations of erasure and undetected error probabilities"
    - "list decoding random coding exponents and expurgated exponents"
    - "expurgated random coding ensembles exponents refinements and connections"
    - "erasure list random coding error exponents are not universally achievable"
    - "erasure list exponents for slepian wolf decoding"

Connected through hyperedge HE-3 (induced by source paper "error and erasure exponents for the broadcast channel with degraded message sets"):
  with members:
    - "on the reliability function of the discrete memoryless relay channel"
    - "achievable error exponents for channel with side information erasure and list decoding"
    - "error exponents for broadcast channels with degraded message sets"
    - "error exponents of erasure list decoding revisited via moments of distance enumerators"

Connected through hyperedge HE-4 (induced by source paper "fixed error asymptotics for erasure and list decoding"):
  with members:
    - "the third order term in the normal approximation for the awgn channel"
    - "list decoding random coding exponents and expurgated exponents"
    - "on the dispersions of three network information theory problems"
    - "a tight upper bound for the third order asymptotics for most discrete memoryless channels"
    - "feedback communication systems with limitations on incremental redundancy"
    - "erasure list exponents for slepian wolf decoding"
    - "reliability based error detection for feedback communication with low latency"
    - "the third order term in the normal approximation for singular channels"

Connected through hyperedge HE-5 (induced by source paper "asymmetric evaluations of erasure and undetected error probabilities"):
  with members:
    - "asymptotic estimates in information theory with non vanishing error probabilities"
    - "list decoding random coding exponents and expurgated exponents"
    - "unequal message protection asymptotic and non asymptotic tradeoffs"
    - "fixed error asymptotics for erasure and list decoding"
    - "erasure list exponents for slepian wolf decoding"
    - "moderate deviations in channel coding"
    - "fixed length lossy compression in the finite blocklength regime"
    - "moderate deviations of lossy source coding for discrete and gaussian sources"

Connected through hyperedge HE-6 (induced by source paper "erasure list random coding error exponents are not universally achievable"):
  with members:
    - "erasure list exponents for slepian wolf decoding"
    - "universal decoding for arbitrary channels relative to a given class of decoding metrics"
    - "multilevel coding for channels with non uniform inputs and rateless transmission over the bsc"

Connected through hyperedge HE-7 (induced by source paper "errors and erasures decoding for block codes with feedback"):
  with members:
    - "variations on a theme by schalkwijk and kailath"
    - "achievable error exponents for channel with side information erasure and list decoding"
    - "error exponents for the gaussian channel with active noisy feedback"
    - "a simple converse of burnashev s reliability function"
    - "error exponents for variable length block codes with feedback and cost constraints"
    - "error exponents of erasure list decoding revisited via moments of distance enumerators"
    - "on the error exponents of arq channels with deadlines"

Connected through hyperedge HE-8 (induced by source paper "achievable error exponents for channel with side information erasure and list decoding"):
  with members:
    - "capacity and random coding exponents for channel coding with side information"

Question: Please tell me which class the center node 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)