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: "n channel entropy constrained multiple description lattice vector quantization"
  Abstract: In this paper, we derive analytical expressions for the central and side quantizers which, under high-resolution assumptions, minimize the expected distortion of a symmetric multiple-description lattice vector quantization (MD-LVQ) system subject to entropy constraints on the side descriptions for given packet-loss probabilities. We consider a special case of the general n-channel symmetric multiple-description problem where only a single parameter controls the redundancy tradeoffs between the central and the side distortions. Previous work on two-channel MD-LVQ showed that the distortions of the side quantizers can be expressed through the normalized second moment of a sphere. We show here that this is also the case for three-channel MD-LVQ. Furthermore, we conjecture that this is true for the general n-channel MD-LVQ. For given source, target rate, and packet-loss probabilities we find the optimal number of descriptions and construct the MD-LVQ system that minimizes the expected distortion. We verify theoretical expressions by numerical simulations and show in a practical setup that significant performance improvements can be achieved over state-of-the-art two-channel MD-LVQ by using three-channel MD-LVQ.

Connected through hyperedge HE-1 (induced by source paper "optimal index assignment for multiple description scalar quantization"):
  with members:
    - "n channel asymmetric entropy constrained multiple description lattice vector quantization"
    - "vector gaussian multiple description with individual and central receivers"
    - "index assignment for multichannel communication under failure"

Connected through hyperedge HE-2 (induced by source paper "n channel asymmetric entropy constrained multiple description lattice vector quantization"):
  with members:
    - "approximating the gaussian multiple description rate region under symmetric distortion constraints"
    - "lattices for distributed source coding jointly gaussian sources and reconstruction of a linear function"
    - "multiple description coding by dithered delta sigma quantization"
    - "multiple description lattice vector quantization"
    - "multiple description quantization via gram schmidt orthogonalization"
    - "vector gaussian multiple description with individual and central receivers"
    - "index assignment for multichannel communication under failure"

Connected through hyperedge HE-3 (induced by source paper "multiple description coding by dithered delta sigma quantization"):
  with members:
    - "achieving the gaussian rate distortion function by prediction"
    - "multiple description lattice vector quantization"
    - "multiple description quantization via gram schmidt orthogonalization"
    - "n channel asymmetric multiple description lattice vector quantization"

Connected through hyperedge HE-4 (induced by source paper "optimal design of multiple description lattice vector quantizers"):
  with members:
    - "index assignment for multichannel communication under failure"

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)