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 technique for deriving one shot achievability results in network information theory"
  Abstract: This paper proposes a novel technique to prove a one-shot version of achievability results in network information theory. The technique is not based on covering and packing lemmas. In this technique, we use an stochastic encoder and decoder with a particular structure for coding that resembles both the ML and the joint-typicality coders. Although stochastic encoders and decoders do not usually enhance the capacity region, their use simplifies the analysis. The Jensen inequality lies at the heart of error analysis, which enables us to deal with the expectation of many terms coming from stochastic encoders and decoders at once. The technique is illustrated via several examples: point-to-point channel coding, Gelfand-Pinsker, Broadcast channel (Marton), Berger-Tung, Heegard-Berger/Kaspi, Multiple description coding and Joint source-channel coding over a MAC. Most of our one-shot results are new. The asymptotic forms of these expressions is the same as that of classical results. Our one-shot bounds in conjunction with multi-dimensional Berry-Essen CLT imply new results in the finite blocklength regime. In particular applying the one-shot result for the memoryless broadcast channel in the asymptotic case, we get the entire region of Marton's inner bound without any need for time-sharing.

Connected through hyperedge HE-1 (induced by source paper "exponential strong converse for successive refinement with causal decoder side information"):
  with members:
    - "strong converse using change of measure arguments"
    - "exponential strong converse for content identification with lossy recovery"
    - "discrete lossy gray wyner revisited second order asymptotics large and moderate deviations"
    - "new strong converse for asymmetric broadcast channels"
    - "a proof of the strong converse theorem for gaussian multiple access channels"
    - "exponent function for one helper source coding problem at rates outside the rate region"
    - "strong successive refinability and rate distortion complexity tradeoff"
    - "asymptotic estimates in information theory with non vanishing error probabilities"

Connected through hyperedge HE-2 (induced by source paper "sharp bounds for mutual covering"):
  with members:
    - "exact soft covering exponent"
    - "a unified framework for one shot achievability via the poisson matching lemma"
    - "strong functional representation lemma and applications to coding theorems"
    - "secret key generation with limited interaction"
    - "the likelihood encoder for lossy compression"
    - "the generalized stochastic likelihood decoder random coding and expurgated bounds"
    - "on non interactive simulation of joint distributions"
    - "one shot mutual covering lemma and marton s inner bound with a common message"

Connected through hyperedge HE-3 (induced by source paper "a lagrange dual lower bound to the error exponent function of the typical random code"):
  with members:
    - "error exponents of typical random trellis codes"
    - "error exponents of typical random codes for the colored gaussian channel"
    - "error exponents of typical random codes"
    - "correction to the generalized stochastic likelihood decoder random coding and expurgated bounds"
    - "the likelihood encoder for lossy compression"
    - "the generalized stochastic likelihood decoder random coding and expurgated bounds"

Connected through hyperedge HE-4 (induced by source paper "a unified framework for one shot achievability via the poisson matching lemma"):
  with members:
    - "minimax learning for remote prediction"
    - "strong functional representation lemma and applications to coding theorems"
    - "the likelihood encoder for lossy compression"
    - "one shot mutual covering lemma and marton s inner bound with a common message"
    - "on the dispersions of the gel fand pinsker channel and dirty paper coding"
    - "non asymptotic output statistics of random binning and its applications"
    - "distributed channel synthesis"
    - "lossy joint source channel coding in the finite blocklength regime"

Connected through hyperedge HE-5 (induced by source paper "second order converses via reverse hypercontractivity"):
  with members:
    - "information theoretic perspectives on brascamp lieb inequality and its reverse"
    - "smoothing brascamp lieb inequalities and strong converses for common randomness generation"
    - "asymptotic estimates in information theory with non vanishing error probabilities"
    - "strong converse exponent for degraded broadcast channels at rates outside the capacity region"
    - "fixed length lossy compression in the finite blocklength regime"
    - "information spectrum approach to second order coding rate in channel coding"
    - "mutual information and minimum mean square error in gaussian channels"

Connected through hyperedge HE-6 (induced by source paper "error exponents of typical random codes for the colored gaussian channel"):
  with members:
    - "error exponents of typical random codes"
    - "the generalized stochastic likelihood decoder random coding and expurgated bounds"
    - "how could the replica method improve accuracy of performance assessment of channel coding"

Connected through hyperedge HE-7 (induced by source paper "false accept false reject trade offs in biometric authentication systems"):
  with members:
    - "the likelihood encoder for lossy compression"
    - "the generalized stochastic likelihood decoder random coding and expurgated bounds"

Connected through hyperedge HE-8 (induced by source paper "second order region for gray wyner network"):
  with members:
    - "discrete lossy gray wyner revisited second order asymptotics large and moderate deviations"
    - "interactive communication for data exchange"
    - "second order asymptotics for the gaussian mac with degraded message sets"
    - "strong successive refinability and rate distortion complexity tradeoff"
    - "asymptotic estimates in information theory with non vanishing error probabilities"
    - "information complexity density and simulation of protocols"
    - "strong converse and second order asymptotics of channel resolvability"
    - "channels with cost constraints strong converse and dispersion"

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)