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 single letter upper bound for the sum rate of multiple access channels with correlated sources"
  Abstract: The capacity region of the multiple access channel with arbitrarily correlated sources remains an open problem. Cover, El Gamal and Salehi gave an achievable region in the form of single-letter entropy and mutual information expressions, without a single-letter converse. Cover, El Gamal and Salehi also gave a converse in terms of some n-letter mutual informations, which are incomputable. In this paper, we derive an upper bound for the sum rate of this channel in a single-letter expression by using spectrum analysis. The incomputability of the sum rate of Cover, El Gamal and Salehi scheme comes from the difficulty of characterizing the possible joint distributions for the n-letter channel inputs. Here we introduce a new data processing inequality, which leads to a single-letter necessary condition for these possible joint distributions. We develop a single-letter upper bound for the sum rate by using this single-letter necessary condition on the possible joint distributions.

Connected through hyperedge HE-1 (induced by source paper "a new data processing inequality and its applications in distributed source and channel coding"):
  with members:
    - "sending a bi variate gaussian source over a gaussian mac"
    - "an outer bound for the multi terminal rate distortion region"
    - "sending a bi variate gaussian source over a gaussian mac"
    - "an infeasibility result for the multiterminal source coding problem"

Connected through hyperedge HE-2 (induced by source paper "sending a bi variate gaussian source over a gaussian mac"):
  with members:
    - "on the gaussian mac with imperfect feedback"
    - "superimposed coded and uncoded transmissions of a gaussian source over the gaussian channel"
    - "rate region of the quadratic gaussian two encoder source coding problem"

Connected through hyperedge HE-3 (induced by source paper "sending a bi variate gaussian source over a gaussian mac"):
  with members:
    - "on the gaussian mac with imperfect feedback"
    - "superimposed coded and uncoded transmissions of a gaussian source over the gaussian channel"
    - "rate region of the quadratic gaussian two encoder source coding problem"

Connected through hyperedge HE-4 (induced by source paper "dense gaussian sensor networks minimum achievable distortion and the order optimality of separation"):
  with members:
    - "optimal distortion power tradeoffs in sensor networks gauss markov random processes"
    - "optimal distortion power tradeoffs in gaussian sensor networks"

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)