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 case where interference does not affect the channel dispersion"
  Abstract: In 1975, Carleial presented a special case of an interference channel in which the interference does not reduce the capacity of the constituent point-to-point Gaussian channels. In this work, we show that if the inequalities in the conditions that Carleial stated are strict, the dispersions are similarly unaffected. More precisely, in this work, we characterize the second-order coding rates of the Gaussian interference channel in the strictly very strong interference regime. In other words, we characterize the speed of convergence of rates of optimal block codes towards a boundary point of the (rectangular) capacity region. These second-order rates are expressed in terms of the average probability of error and variances of some modified information densities which coincide with the dispersion of the (single-user) Gaussian channel. We thus conclude that the dispersions are unaffected by interference in this channel model.

Connected through hyperedge HE-1 (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"

Connected through hyperedge HE-2 (induced by source paper "strong converses are just edge removal properties"):
  with members:
    - "on the impact of a single edge on the network coding capacity"
    - "on the capacity advantage of a single bit"
    - "smoothing brascamp lieb inequalities and strong converses for common randomness generation"
    - "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 converse exponent for degraded broadcast channels at rates outside the capacity region"
    - "strong converse theorems for degraded broadcast channels with feedback"
    - "equivalence for networks with adversarial state"

Connected through hyperedge HE-3 (induced by source paper "second order and moderate deviation asymptotics for successive refinement"):
  with members:
    - "second order region for gray wyner network"
    - "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"
    - "second order coding rates for channels with state"
    - "on the dispersions of three network information theory problems"
    - "on the dispersions of the gel fand pinsker channel and dirty paper coding"
    - "moderate deviations in channel coding"

Connected through hyperedge HE-4 (induced by source paper "a proof of the strong converse theorem for gaussian multiple access channels"):
  with members:
    - "asymptotic estimates in information theory with non vanishing error probabilities"
    - "on the dispersions of three network information theory problems"
    - "second order rate region of constant composition codes for the multiple access channel"
    - "a finite blocklength perspective on gaussian multi access channels"
    - "information spectrum approach to second order coding rate in channel coding"
    - "simple channel coding bounds"

Connected through hyperedge HE-5 (induced by source paper "the dispersion of nearest neighbor decoding for additive non gaussian channels"):
  with members:
    - "optimal achievable rates for interference networks with random codes"
    - "asymptotic estimates in information theory with non vanishing error probabilities"
    - "the third order term in the normal approximation for the awgn channel"
    - "asymptotics and non asymptotics for universal fixed to variable source coding"
    - "fixed length lossy compression in the finite blocklength regime"
    - "information spectrum approach to second order coding rate in channel coding"

Connected through hyperedge HE-6 (induced by source paper "second order rate region of constant composition codes for the multiple access channel"):
  with members:
    - "second order asymptotics for the gaussian mac with degraded message sets"
    - "on the dispersions of three network information theory problems"
    - "a finite blocklength perspective on gaussian multi access channels"
    - "moderate deviations in channel coding"
    - "second order slepian wolf coding theorems for non mixed and mixed sources"
    - "information spectrum approach to second order coding rate in channel coding"

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)