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: "distributed source coding of correlated gaussian remote sources"
  Abstract: We consider the distributed source coding system for $L$ correlated Gaussian observations $Y_i, i=1,2, ..., L$. Let $X_i,i=1,2, ..., L$ be $L$ correlated Gaussian random variables and $N_i,$ $i=1,2,... L$ be independent additive Gaussian noises also independent of $X_i, i=1,2,..., L$. We consider the case where for each $i=1,2,..., L$, $Y_i$ is a noisy observation of $X_i$, that is, $Y_i=X_i+N_i$. On this coding system the determination problem of the rate distortion region remains open. In this paper, we derive explicit outer and inner bounds of the rate distortion region. We further find an explicit sufficient condition for those two to match. We also study the sum rate part of the rate distortion region when the correlation has some symmetrical property and derive a new lower bound of the sum rate part. We derive a sufficient condition for this lower bound to be tight. The derived sufficient condition depends only on the correlation property of the sources and their observations.

Connected through hyperedge HE-1 (induced by source paper "successive wyner ziv coding for the binary ceo problem under log loss"):
  with members:
    - "analysis and code design for the binary ceo problem under logarithmic loss"
    - "multiterminal source coding under logarithmic loss"
    - "successive wyner ziv coding scheme and its application to the quadratic gaussian ceo problem"
    - "binary quantization using belief propagation with decimation over factor graphs of ldgm codes"

Connected through hyperedge HE-2 (induced by source paper "binary ceo problem under log loss with bsc test channel model"):
  with members:
    - "analysis and code design for the binary ceo problem under logarithmic loss"
    - "universality of logarithmic loss in lossy compression"
    - "multiterminal source coding under logarithmic loss"
    - "successive wyner ziv coding scheme and its application to the quadratic gaussian ceo problem"

Connected through hyperedge HE-3 (induced by source paper "analysis and code design for the binary ceo problem under logarithmic loss"):
  with members:
    - "universality of logarithmic loss in lossy compression"
    - "multiterminal source coding under logarithmic loss"
    - "successive wyner ziv coding scheme and its application to the quadratic gaussian ceo problem"

Connected through hyperedge HE-4 (induced by source paper "distributed source coding of correlated gaussian sources"):
  with members:
    - "rate region of the quadratic gaussian two encoder source coding problem"

Connected through hyperedge HE-5 (induced by source paper "lattices for distributed source coding jointly gaussian sources and reconstruction of a linear function"):
  with members:
    - "the gaussian many help one distributed source coding problem"
    - "multiple description lattice vector quantization"
    - "unified theory of source coding part ii multiterminal problems"
    - "rate region of the quadratic gaussian two encoder source coding problem"

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)