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: "convergence of the min sum message passing algorithm for quadratic optimization"
  Abstract: We establish the convergence of the min-sum message passing algorithm for minimization of a broad class of quadratic objective functions: those that admit a convex decomposition. Our results also apply to the equivalent problem of the convergence of Gaussian belief propagation.

Connected through hyperedge HE-1 (induced by source paper "message passing algorithms reparameterizations and splittings"):
  with members:
    - "loopy belief propagation for approximate inference an empirical study"
    - "counting in graph covers a combinatorial characterization of the bethe entropy function"
    - "map estimation linear programming and belief propagation with convex free energies"
    - "convergent message passing algorithms a unifying view"
    - "on the optimality of tree reweighted max product message passing"
    - "message passing for maximum weight independent set"
    - "norm product belief propagation primal dual message passing for approximate inference"
    - "towards low complexity linear programming decoding"

Connected through hyperedge HE-2 (induced by source paper "belief propagation for weighted b matchings on arbitrary graphs and its relation to linear programs with integer solutions"):
  with members:
    - "map estimation linear programming and belief propagation with convex free energies"
    - "map estimation message passing and perfect graphs"
    - "a new class of upper bounds on the log partition function"
    - "message passing for maximum weight independent set"
    - "max product for maximum weight matching convergence correctness and lp duality"
    - "equivalence of lp relaxation and max product for weighted matching in general graphs"
    - "on the solution space geometry of random constraint satisfaction problems"
    - "graph cover decoding and finite length analysis of message passing iterative decoding of ldpc codes"

Connected through hyperedge HE-3 (induced by source paper "belief propagation for min cost network flow convergence and correctness"):
  with members:
    - "message passing for maximum weight independent set"
    - "max product for maximum weight matching convergence correctness and lp duality"
    - "solving constraint satisfaction problems through belief propagation guided decimation"

Connected through hyperedge HE-4 (induced by source paper "message passing for maximum weight independent set"):
  with members:
    - "map estimation linear programming and belief propagation with convex free energies"
    - "on the optimality of tree reweighted max product message passing"
    - "belief propagation for weighted b matchings on arbitrary graphs and its relation to linear programs with integer solutions"
    - "max product for maximum weight matching convergence correctness and lp duality"
    - "convergence of min sum message passing for quadratic optimization"

Connected through hyperedge HE-5 (induced by source paper "interior point algorithms for linear programming decoding"):
  with members:
    - "interior point decoding for linear vector channels"
    - "pseudo codeword landscape"
    - "guessing facets polytope structure and improved lp decoder"
    - "graph cover decoding and finite length analysis of message passing iterative decoding of ldpc codes"

Connected through hyperedge HE-6 (induced by source paper "local approximate inference algorithms"):
  with members:
    - "max product for maximum weight matching convergence correctness and lp duality"

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)