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 finite blocklength perspective on gaussian multi access channels"
  Abstract: Motivated by the growing application of wireless multi-access networks with stringent delay constraints, we investigate the Gaussian multiple access channel (MAC) in the finite blocklength regime. Building upon information spectrum concepts, we develop several non-asymptotic inner bounds on channel coding rates over the Gaussian MAC with a given finite blocklength, positive average error probability, and maximal power constraints. Employing Central Limit Theorem (CLT) approximations, we also obtain achievable second-order coding rates for the Gaussian MAC based on an explicit expression for its dispersion matrix. We observe that, unlike the pentagon shape of the asymptotic capacity region, the second-order region has a curved shape with no sharp corners. #R##N#A main emphasis of the paper is to provide a new perspective on the procedure of handling input cost constraints for tight achievability proofs. Contrary to the complicated achievability techniques in the literature, we show that with a proper choice of input distribution, tight bounds can be achieved via the standard random coding argument and a modified typicality decoding. In particular, we prove that codebooks generated randomly according to independent uniform distributions on the respective "power shells" perform far better than both independent and identically distributed (i.i.d.) Gaussian inputs and TDMA with power control. Interestingly, analogous to an error exponent result of Gallager, the resulting achievable region lies roughly halfway between that of the i.i.d. Gaussian inputs and that of a hypothetical "sum-power shell" input. However, dealing with such a non-i.i.d. input requires additional analysis such as a new change of measure technique and application of a Berry-Esseen CLT for functions of random variables.

Connected through hyperedge HE-1 (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"
    - "a case where interference does not affect the channel dispersion"
    - "on the dispersions of three network information theory problems"
    - "second order rate region of constant composition codes for the multiple access channel"
    - "information spectrum approach to second order coding rate in channel coding"
    - "simple channel coding bounds"

Connected through hyperedge HE-2 (induced by source paper "asymptotic estimates in information theory with non vanishing error probabilities"):
  with members:
    - "second order asymptotics for the gaussian mac with degraded message sets"
    - "the third order term in the normal approximation for the awgn channel"
    - "strong converse and second order asymptotics of channel resolvability"
    - "channels with cost constraints strong converse and dispersion"
    - "secret key agreement general capacity and second order asymptotics"
    - "second order coding rates for channels with state"
    - "unequal message protection asymptotic and non asymptotic tradeoffs"
    - "information spectrum approach to strong converse theorems for degraded wiretap channels"

Connected through hyperedge HE-3 (induced by source paper "second order asymptotics for the gaussian mac with degraded message sets"):
  with members:
    - "asymptotic estimates in information theory with non vanishing error probabilities"
    - "the third order term in the normal approximation for the awgn channel"
    - "on the dispersions of three network information theory problems"
    - "second order asymptotics for the discrete memoryless mac with degraded message sets"
    - "mismatched decoding error exponents second order rates and saddlepoint approximations"
    - "second order resolvability intrinsic randomness and fixed length source coding for mixed sources information spectrum approach"
    - "second order rate region of constant composition codes for the multiple access channel"
    - "non asymptotic and second order achievability bounds for coding with side information"

Connected through hyperedge HE-4 (induced by source paper "the third order term in the normal approximation for the awgn channel"):
  with members:
    - "second order asymptotics for the gaussian mac with degraded message sets"
    - "a tight upper bound for the third order asymptotics for most discrete memoryless channels"
    - "mismatched decoding error exponents second order rates and saddlepoint approximations"
    - "refinement of the random coding bound"
    - "a derivation of the asymptotic random coding prefactor"
    - "the third order term in the normal approximation for singular channels"
    - "the log volume of optimal codes for memoryless channels asymptotically within a few nats"
    - "refinement of the sphere packing bound asymmetric channels"

Connected through hyperedge HE-5 (induced by source paper "a case where interference does not affect the channel dispersion"):
  with members:
    - "second order asymptotics for the gaussian mac with degraded message sets"
    - "the third order term in the normal approximation for the awgn channel"
    - "second order coding rates for channels with state"
    - "on the dispersions of three network information theory problems"
    - "a tight upper bound for the third order asymptotics for most discrete memoryless channels"
    - "second order rate region of constant composition codes for the multiple access channel"
    - "non asymptotic and second order achievability bounds for coding with side information"
    - "lossy joint source channel coding in the finite blocklength regime"

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

Connected through hyperedge HE-7 (induced by source paper "on the dispersions of the gel fand pinsker channel and dirty paper coding"):
  with members:
    - "second order asymptotics for the gaussian mac with degraded message sets"
    - "second order coding rates for channels with state"
    - "on the dispersions of three network information theory problems"
    - "a technique for deriving one shot achievability results in network information theory"
    - "non asymptotic output statistics of random binning and its applications"
    - "second order rate region of constant composition codes for the multiple access channel"
    - "non asymptotic and second order achievability bounds for coding with side information"
    - "the gelfand pinsker channel strong converse and upper bound for the reliability function"

Connected through hyperedge HE-8 (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"
    - "a case where interference does not affect the channel dispersion"
    - "on the dispersions of three network information theory problems"
    - "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)