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: "lattice quantization with side information codes asymptotics and applications in sensor networks"
  Abstract: We consider the problem of rate/distortion with side information available only at the decoder. For the case of jointly-Gaussian source X and side information Y, and mean-squared error distortion, Wyner proved in 1976 that the rate/distortion function for this problem is identical to the conditional rate/distortion function R_{X|Y}, assuming the side information Y is available at the encoder. In this paper we construct a structured class of asymptotically optimal quantizers for this problem: under the assumption of high correlation between source X and side information Y, we show there exist quantizers within our class whose performance comes arbitrarily close to Wyner's bound. As an application illustrating the relevance of the high-correlation asymptotics, we also explore the use of these quantizers in the context of a problem of data compression for sensor networks, in a setup involving a large number of devices collecting highly correlated measurements within a confined area. An important feature of our formulation is that, although the per-node throughput of the network tends to zero as network size increases, so does the amount of information generated by each transmitter. This is a situation likely to be encountered often in practice, which allows us to cast under new--and more ``optimistic''--light some negative results on the transport capacity of large-scale wireless networks.

Connected through hyperedge HE-1 (induced by source paper "lattice based robust distributed source coding"):
  with members:
    - "robust distributed source coding"
    - "vector gaussian multiple description with individual and central receivers"
    - "rate region of the quadratic gaussian two encoder source coding problem"

Connected through hyperedge HE-2 (induced by source paper "secure multiterminal source coding with side information at the eavesdropper"):
  with members:
    - "rate distortion with side information at many decoders"
    - "information theoretic proofs of entropy power inequalities"
    - "achieving the secrecy capacity of wiretap channels using polar codes"
    - "rate region of the gaussian scalar help vector source coding problem"
    - "secure lossy source coding with side information at the decoders"
    - "construction of wiretap codes from ordinary channel codes"
    - "lecture notes on network information theory"
    - "secure source coding with a helper"

Connected through hyperedge HE-3 (induced by source paper "data processing bounds for scalar lossy source codes with side information at the decoder"):
  with members:
    - "structure theorems for real time variable rate coding with and without side information"
    - "data processing theorems and the second law of thermodynamics"
    - "efficient on line schemes for encoding individual sequences with side information at the decoder"

Connected through hyperedge HE-4 (induced by source paper "on superposition coding for the wyner ziv problem"):
  with members:
    - "binary quantization using belief propagation with decimation over factor graphs of ldgm codes"
    - "lossy source encoding via message passing and decimation over generalized codewords of ldgm codes"
    - "iterative quantization using codes on graphs"

Connected through hyperedge HE-5 (induced by source paper "distributed joint source channel coding on a multiple access channel with side information"):
  with members:
    - "sending a bivariate gaussian source over a gaussian mac with feedback"
    - "sending a bi variate gaussian source over a gaussian mac"
    - "sending a bi variate gaussian source over a gaussian mac"
    - "coding for the feedback gel fand pinsker channel and the feedforward wyner ziv source"
    - "network information flow with correlated sources"
    - "rate region of the quadratic gaussian two encoder source coding problem"

Connected through hyperedge HE-6 (induced by source paper "distributed joint source channel coding on a multiple access channel with side information"):
  with members:
    - "sending a bivariate gaussian source over a gaussian mac with feedback"
    - "sending a bi variate gaussian source over a gaussian mac"
    - "sending a bi variate gaussian source over a gaussian mac"

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)