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 successive refinement for the kaspi heegard berger problem"
  Abstract: Consider a source that produces independent copies of a triplet of jointly distributed random variables, $\{X_{i},Y_{i},Z_{i}\}_{i=1}^{\infty}$. The process $\{X_{i}\}$ is observed at the encoder, and is supposed to be reproduced at two decoders, where $\{Y_{i}\}$ and $\{Z_{i}\}$ are observed, in either a causal or non-causal manner. The communication between the encoder and the decoders is carried in two successive stages. In the first stage, the transmission is available to both decoders and the source is reconstructed according to the received bit-stream and the individual side information (SI). In the second stage, additional information is sent to both decoders and the source reconstructions are refined according to the transmissions at both stages and the available SI. It is desired to find the necessary and sufficient conditions on the communication rates between the encoder and decoders, so that the distortions incurred (at each stage) will not exceed given thresholds. For the case of non-degraded causal SI at the decoders, an exact single-letter characterization of the achievable region is derived for the case of pure source-coding. Then, for the case of communication carried over independent DMS's with random states known causally/non-causally at the encoder and with causal SI about the source at the decoders, a single-letter characterization of all achievable distortion in both stages is provided and it is shown that the separation theorem holds. Finally, for non-causal degraded SI, inner and outer bounds to the achievable rate-distortion region are derived. These bounds are shown to be tight for certain cases of reconstruction requirements at the decoders, thereby shading some light on the problem of successive refinement with non-degraded SI at the decoders.

Connected through hyperedge HE-1 (induced by source paper "exponential strong converse for successive refinement with causal decoder side information"):
  with members:
    - "strong converse using change of measure arguments"
    - "exponential strong converse for content identification with lossy recovery"
    - "discrete lossy gray wyner revisited second order asymptotics large and moderate deviations"
    - "new strong converse for asymmetric broadcast channels"
    - "a proof of the strong converse theorem for gaussian multiple access channels"
    - "exponent function for one helper source coding problem at rates outside the rate region"
    - "strong successive refinability and rate distortion complexity tradeoff"
    - "asymptotic estimates in information theory with non vanishing error probabilities"

Connected through hyperedge HE-2 (induced by source paper "source coding when the side information may be delayed"):
  with members:
    - "computable bounds for rate distortion with feed forward for stationary and ergodic sources"
    - "interpretations of directed information in portfolio theory data compression and hypothesis testing"
    - "coding for the feedback gel fand pinsker channel and the feedforward wyner ziv source"

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)