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: "gaussian belief propagation solver for systems of linear equations"
  Abstract: The canonical problem of solving a system of linear equations arises in numerous contexts in information theory, communication theory, and related fields. In this contribution, we develop a solution based upon Gaussian belief propagation (GaBP) that does not involve direct matrix inversion. The iterative nature of our approach allows for a distributed message-passing implementation of the solution algorithm. We also address some properties of the GaBP solver, including convergence, exactness, its max-product version and relation to classical solution methods. The application example of decorrelation in CDMA is used to demonstrate the faster convergence rate of the proposed solver in comparison to conventional linear-algebraic iterative solution methods.

Connected through hyperedge HE-1 (induced by source paper "distributed convergence verification for gaussian belief propagation"):
  with members:
    - "convergence analysis of the information matrix in gaussian belief propagation"
    - "convergence analysis of belief propagation for pairwise linear gaussian models"
    - "distributed hybrid power state estimation under pmu sampling phase errors"
    - "distributed clock skew and offset estimation in wireless sensor networks asynchronous algorithm and convergence analysis"
    - "low complexity detection in large dimension mimo isi channels using graphical models"

Connected through hyperedge HE-2 (induced by source paper "convergence analysis of belief propagation for pairwise linear gaussian models"):
  with members:
    - "convergence analysis of the information matrix in gaussian belief propagation"
    - "distributed convergence verification for gaussian belief propagation"
    - "distributed clock skew and offset estimation in wireless sensor networks asynchronous algorithm and convergence analysis"

Connected through hyperedge HE-3 (induced by source paper "convergence analysis of the information matrix in gaussian belief propagation"):
  with members:
    - "distributed clock skew and offset estimation in wireless sensor networks asynchronous algorithm and convergence analysis"

Connected through hyperedge HE-4 (induced by source paper "a graphical model formulation of collaborative filtering neighbourhood methods with fast maximum entropy training"):
  with members:
    - "constrained approximate maximum entropy learning of markov random fields"
    - "projected subgradient methods for learning sparse gaussians"
    - "properties of bethe free energies and message passing in gaussian models"

Connected through hyperedge HE-5 (induced by source paper "discrete geometric analysis of message passing algorithm on graphs"):
  with members:
    - "loopy belief propagation for approximate inference an empirical study"
    - "expectation propagation for approximate bayesian inference"
    - "belief optimization for binary networks a stable alternative to loopy belief propagation"
    - "graph zeta function in the bethe free energy and loopy belief propagation"
    - "approximate inference on planar graphs using loop calculus and belief propagation"
    - "belief propagation and beyond for particle tracking"
    - "polynomial linear programming with gaussian belief propagation"
    - "pseudo codewords of cycle codes via zeta functions"

Connected through hyperedge HE-6 (induced by source paper "a low density lattice decoder via non parametric belief propagation"):
  with members:
    - "fixing convergence of gaussian belief propagation"
    - "gaussian belief propagation based multiuser detection"
    - "gaussian belief propagation theory and application"
    - "message passing decoding of lattices using gaussian mixtures"
    - "bayesian compressive sensing via belief propagation"
    - "low density lattice codes"

Connected through hyperedge HE-7 (induced by source paper "fixing convergence of gaussian belief propagation"):
  with members:
    - "a gaussian belief propagation solver for large scale support vector machines"
    - "gaussian belief propagation based multiuser detection"
    - "distributed kalman filter via gaussian belief propagation"
    - "polynomial linear programming with gaussian belief propagation"
    - "belief propagation based multi user detection"

Connected through hyperedge HE-8 (induced by source paper "distributed large scale network utility maximization"):
  with members:
    - "fixing convergence of gaussian belief propagation"
    - "gaussian belief propagation based multiuser detection"
    - "polynomial linear programming with gaussian belief propagation"

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)