human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "robust distributed compression of symmetrically correlated gaussian sources"):
  Abstract: Consider a lossy compression system with $\ell$ distributed encoders and a centralized decoder. Each encoder compresses its observed source and forwards the compressed data to the decoder for joint reconstruction of the target signals under the mean squared error distortion constraint. It is assumed that the observed sources can be expressed as the sum of the target signals and the corruptive noises, which are generated independently from two symmetric multivariate Gaussian distributions. Depending on the parameters of such distributions, the rate-distortion limit of this system is characterized either completely or at least for sufficiently low distortions. The results are further extended to the robust distributed compression setting, where the outputs of a subset of encoders may also be used to produce a non-trivial reconstruction of the corresponding target signals. In particular, we obtain in the high-resolution regime a precise characterization of the minimum achievable reconstruction distortion based on the outputs of $k+1$ or more encoders when every $k$ out of all $\ell$ encoders are operated collectively in the same mode that is greedy in the sense of minimizing the distortion incurred by the reconstruction of the corresponding $k$ target signals with respect to the average rate of these $k$ encoders.

Includes members:
  Member "generalized gaussian multiterminal source coding the symmetric case":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "generalized gaussian multiterminal source coding in the high resolution regime")
  Member "the sum rate of vector gaussian multiple description coding with tree structured covariance distortion constraints":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "vector gaussian successive refinement with degraded side information")
  Member "successive wyner ziv coding scheme and its application to the quadratic gaussian ceo problem":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fundamental limits of distributed tracking")
  Member "multiuser successive refinement and multiple description coding":
    also connected through other hyperedges:
      (none)
  Member "multiple description quantization via gram schmidt orthogonalization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "successive wyner ziv coding for the binary ceo problem under logarithmic loss")
  Member "robust distributed source coding":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "generalized gaussian multiterminal source coding in the high resolution regime")
  Member "vector gaussian multiple description with individual and central receivers":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "vector gaussian successive refinement with degraded side information")
  Member "rate region of the quadratic gaussian two encoder source coding problem":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "integer forcing architectures for uplink cloud radio access networks")

Question: Please tell me which class the source paper 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)