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: "an achievable rate distortion region for the multiple descriptions problem"
  Abstract: A multiple-descriptions (MD) coding strategy is proposed and an inner bound to the achievable rate-distortion region is derived. The scheme utilizes linear codes. It is shown in two different MD set-ups that the linear coding scheme achieves a larger rate-distortion region than previously known random coding strategies. Furthermore, it is shown via an example that the best known random coding scheme for the set-up can be improved by including additional randomly generated codebooks.

Connected through hyperedge HE-1 (induced by source paper "communicating correlated sources over mac and interference channels i separation based schemes"):
  with members:
    - "communicating correlated sources over an interference channel"
    - "broadcasting correlated vector gaussians"
    - "matched multiuser gaussian source channel communications via uncoded schemes"
    - "on joint source channel coding for correlated sources over multiple access relay channels"
    - "a new data processing inequality and its applications in distributed source and channel coding"
    - "optimality and approximate optimality of source channel separation in networks"
    - "interference channels with arbitrarily correlated sources"
    - "distributed joint source channel coding on a multiple access channel with side information"

Connected through hyperedge HE-2 (induced by source paper "trade off between communication and cooperation in the interference channel"):
  with members:
    - "an achievable rate distortion region for multiple descriptions source coding based on coset codes"
    - "sub optimality of the han kobayashi achievable region for interference channels"
    - "on interference networks over finite fields"
    - "achievable rate region for three user discrete broadcast channel based on coset codes"
    - "the approximate capacity of the many to one and one to many gaussian interference channels"

Connected through hyperedge HE-3 (induced by source paper "an achievable rate distortion region for multiple descriptions source coding based on coset codes"):
  with members:
    - "combinatorial message sharing and a new achievable region for multiple descriptions"
    - "achievable rate region for three user discrete broadcast channel based on coset codes"

Connected through hyperedge HE-4 (induced by source paper "combinatorial message sharing and a new achievable region for multiple descriptions"):
  with members:
    - "on the role of common codewords in quadratic gaussian multiple descriptions coding"
    - "a strictly improved achievable region for multiple descriptions using combinatorial message sharing"
    - "asymmetric multilevel diversity coding and asymmetric gaussian multiple descriptions"
    - "approximating the gaussian multiple description rate region under symmetric distortion constraints"
    - "vector gaussian multiple description with individual and central receivers"

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)