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: "generalized gaussian multiterminal source coding the symmetric case"
  Abstract: Consider a generalized multiterminal source coding system, where $\ell\choose m$ encoders, each observing a distinct size-$m$ subset of $\ell$ ($\ell\geq 2$) zero-mean unit-variance symmetrically correlated Gaussian sources with correlation coefficient $\rho$, compress their observations in such a way that a joint decoder can reconstruct the sources within a prescribed mean squared error distortion based on the compressed data. The optimal rate-distortion performance of this system was previously known only for the two extreme cases $m=\ell$ (the centralized case) and $m=1$ (the distributed case), and except when $\rho=0$, the centralized system can achieve strictly lower compression rates than the distributed system under all non-trivial distortion constraints. Somewhat surprisingly, it is established in the present paper that the optimal rate-distortion performance of the afore-described generalized multiterminal source coding system with $m\geq 2$ coincides with that of the centralized system for all distortions when $\rho\leq 0$ and for distortions below an explicit positive threshold (depending on $m$) when $\rho>0$. Moreover, when $\rho>0$, the minimum achievable rate of generalized multiterminal source coding subject to an arbitrary positive distortion constraint $d$ is shown to be within a finite gap (depending on $m$ and $d$) from its centralized counterpart in the large $\ell$ limit except for possibly the critical distortion $d=1-\rho$.

Connected through hyperedge HE-1 (induced by source paper "generalized gaussian multiterminal source coding in the high resolution regime"):
  with members:
    - "robust distributed compression of symmetrically correlated gaussian sources"
    - "successive wyner ziv coding scheme and its application to the quadratic gaussian ceo problem"
    - "robust distributed source coding"
    - "rate region of the quadratic gaussian two encoder source coding problem"

Connected through hyperedge HE-2 (induced by source paper "robust distributed compression of symmetrically correlated gaussian sources"):
  with members:
    - "the sum rate of vector gaussian multiple description coding with tree structured covariance distortion constraints"
    - "successive wyner ziv coding scheme and its application to the quadratic gaussian ceo problem"
    - "multiuser successive refinement and multiple description coding"
    - "multiple description quantization via gram schmidt orthogonalization"
    - "robust distributed source coding"
    - "vector gaussian multiple description with individual and central receivers"
    - "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)