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: "on the dispersions of three network information theory problems"
  Abstract: We analyze the dispersions of distributed lossless source coding (the Slepian-Wolf problem), the multiple-access channel, and the asymmetric broadcast channel. For the two-encoder Slepian-Wolf problem, we introduce a quantity known as the entropy dispersion matrix, which is analogous to the scalar dispersions that have gained interest recently. We prove a global dispersion result that can be expressed in terms of this entropy dispersion matrix and provides intuition on the approximate rate losses at a given blocklength and error probability. To gain better intuition about the rate at which the nonasymptotic rate region converges to the Slepian-Wolf boundary, we define and characterize two operational dispersions: 1) the local dispersion and 2) the weighted sum-rate dispersion. The former represents the rate of convergence to a point on the Slepian-Wolf boundary, whereas the latter represents the fastest rate for which a weighted sum of the two rates converges to its asymptotic fundamental limit. Interestingly, when we approach either of the two corner points, the local dispersion is characterized not by a univariate Gaussian, but a bivariate one as well as a subset of off-diagonal elements of the aforementioned entropy dispersion matrix. Finally, we demonstrate the versatility of our achievability proof technique by providing inner bounds for the multiple-access channel and the asymmetric broadcast channel in terms of dispersion matrices. All our proofs are unified by a so-called vector rate redundancy theorem, which is proved using the multidimensional Berry-Esseen theorem.

Connected through hyperedge HE-1 (induced by source paper "gaussian multiple and random access in the finite blocklength regime"):
  with members:
    - "fundamental limits of many user mac with finite payloads and fading"
    - "lossless source coding in the point to point multiple access and random access scenarios"
    - "random access channel coding in the finite blocklength regime"
    - "capacity of gaussian many access channels"
    - "a proof of the strong converse theorem for gaussian multiple access channels"
    - "the third order term in the normal approximation for the awgn channel"
    - "many access channels the gaussian case with random user activities"
    - "second order rate region of constant composition codes for the multiple access channel"

Connected through hyperedge HE-2 (induced by source paper "lossless source coding in the point to point multiple access and random access scenarios"):
  with members:
    - "random access channel coding in the finite blocklength regime"
    - "on the calculation of the minimax converse of the channel coding problem"
    - "variable length compression allowing errors"
    - "random access an information theoretic perspective"
    - "lossy joint source channel coding in the finite blocklength regime"
    - "second order slepian wolf coding theorems for non mixed and mixed sources"
    - "fixed length lossy compression in the finite blocklength regime"
    - "network coding is zero error always possible"

Connected through hyperedge HE-3 (induced by source paper "the dispersion of the gauss markov source"):
  with members:
    - "second order region for gray wyner network"
    - "lossy joint source channel coding in the finite blocklength regime"
    - "fixed length lossy compression in the finite blocklength regime"
    - "the dispersion of lossy source coding"
    - "the dispersion of joint source channel coding"
    - "a note on rate distortion functions for nonstationary gaussian autoregressive processes"

Connected through hyperedge HE-4 (induced by source paper "fundamental limits of lossless data compression with side information"):
  with members:
    - "lossless source coding in the point to point multiple access and random access scenarios"
    - "improved finite blocklength converses for slepian wolf coding via linear programming"
    - "reference based genome compression"
    - "second order slepian wolf coding theorems for non mixed and mixed sources"

Connected through hyperedge HE-5 (induced by source paper "random access channel coding in the finite blocklength regime"):
  with members:
    - "lossless source coding in the point to point multiple access and random access scenarios"
    - "capacity of gaussian many access channels"
    - "a proof of the strong converse theorem for gaussian multiple access channels"
    - "many access channels the gaussian case with random user activities"
    - "aloha random access that operates as a rateless code"
    - "second order rate region of constant composition codes for the multiple access channel"
    - "random access an information theoretic perspective"

Connected through hyperedge HE-6 (induced by source paper "first and second order hypothesis testing for mixed memoryless sources"):
  with members:
    - "second order region for gray wyner network"
    - "first and second order coding theorems for mixed memoryless channels with general mixture"
    - "second order resolvability intrinsic randomness and fixed length source coding for mixed sources information spectrum approach"
    - "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 "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-8 (induced by source paper "a unified approach to source and message compression"):
  with members:
    - "a one shot achievability result for quantum state redistribution"
    - "wiretap channels with random states non causally available at the encoder"
    - "simple one shot bounds for various source coding problems using smooth renyi quantities"
    - "a technique for deriving one shot achievability results in network information theory"
    - "distributed channel synthesis"
    - "fixed length lossy compression in the finite blocklength regime"
    - "information equals amortized communication"
    - "communication requirements for generating correlated random variables"

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)