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: "multiple description quantization via gram schmidt orthogonalization"
  Abstract: The multiple description (MD) problem has received considerable attention as a model of information transmission over unreliable channels. A general framework for designing efficient MD quantization schemes is proposed in this paper. We provide a systematic treatment of the El Gamal-Cover (EGC) achievable MD rate-distortion region, and show it can be decomposed into a simplified-EGC (SEGC) region and a superimposed refinement operation. Furthermore, any point in the SEGC region can be achieved via a successive quantization scheme along with quantization splitting. For the quadratic Gaussian case, the proposed scheme has an intrinsic connection with the Gram-Schmidt orthogonalization, which implies that the whole Gaussian MD rate-distortion region is achievable with a sequential dithered lattice-based quantization scheme as the dimension of the (optimal) lattice quantizers becomes large. Moreover, this scheme is shown to be universal for all independent and identically distributed (i.i.d.) smooth sources with performance no worse than that for an i.i.d. Gaussian source with the same variance and asymptotically optimal at high resolution. A class of MD scalar quantizers in the proposed general framework is also constructed and is illustrated geometrically; the performance is analyzed in the high-resolution regime, which exhibits a noticeable improvement over the existing MD scalar quantization schemes

Connected through hyperedge HE-1 (induced by source paper "successive wyner ziv coding for the binary ceo problem under logarithmic loss"):
  with members:
    - "successive wyner ziv coding for the binary ceo problem under log loss"
    - "analysis and code design for the binary ceo problem under logarithmic loss"
    - "remote source coding under gaussian noise dueling roles of power and entropy power"
    - "the ceo problem with rth power of difference and logarithmic distortions"
    - "on the optimal fronthaul compression and decoding strategies for uplink cloud radio access networks"
    - "the non regular ceo problem"
    - "how to achieve the capacity of asymmetric channels"
    - "multiterminal source coding under logarithmic loss"

Connected through hyperedge HE-2 (induced by source paper "robust distributed compression of symmetrically correlated gaussian sources"):
  with members:
    - "generalized gaussian multiterminal source coding the symmetric case"
    - "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"
    - "robust distributed source coding"
    - "vector gaussian multiple description with individual and central receivers"
    - "rate region of the quadratic gaussian two encoder source coding problem"

Connected through hyperedge HE-3 (induced by source paper "universal quantization for separate encodings and joint decoding of correlated sources"):
  with members:
    - "zero delay and causal single user and multi user lossy source coding with decoder side information"
    - "multiterminal source coding under logarithmic loss"
    - "rate region of the quadratic gaussian two encoder source coding problem"

Connected through hyperedge HE-4 (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"
    - "n channel 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-5 (induced by source paper "colored gaussian multiple descriptions spectral domain characterization and time domain design"):
  with members:
    - "achieving the gaussian rate distortion function by prediction"
    - "multiple description coding by dithered delta sigma quantization"
    - "on the role of mmse estimation in approaching the information theoretic limits of linear gaussian channels shannon meets wiener"

Connected through hyperedge HE-6 (induced by source paper "approximating the gaussian multiple description rate region under symmetric distortion constraints"):
  with members:
    - "a new outer bound and the noisy interference sum rate capacity for gaussian interference channels"
    - "approximate capacity of gaussian relay networks"
    - "gaussian interference channel capacity to within one bit"
    - "wireless network information flow"
    - "vector gaussian multiple description with individual and central receivers"

Connected through hyperedge HE-7 (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"
    - "n channel entropy constrained multiple description lattice vector quantization"
    - "n channel asymmetric multiple description lattice vector quantization"

Connected through hyperedge HE-8 (induced by source paper "multiuser successive refinement and multiple description coding"):
  with members:
    - "on multistage successive refinement for wyner ziv source coding with degraded side informations"
    - "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)