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: "max product belief propagation for linear programming applications to combinatorial optimization"
  Abstract: Max-product belief propagation (BP) is a popular message-passing algorithm for computing a maximum-a-posteriori (MAP) assignment in a joint distribution represented by a graphical model (GM). It has been shown that BP can solve a few classes of Linear Programming (LP) formulations to combinatorial optimization problems including maximum weight matching and shortest path, i.e., BP can be a distributed solver for certain LPs. However, those LPs and corresponding BP analysis are very sensitive to underlying problem setups, and it has been not clear what extent these results can be generalized to. In this paper, we obtain a generic criteria that BP converges to the optimal solution of given LP, and show that it is satisfied in LP formulations associated to many classical combinatorial optimization problems including maximum weight perfect matching, shortest path, traveling salesman, cycle packing and vertex cover. More importantly, our criteria can guide the BP design to compute fractional LP solutions, while most prior results focus on integral ones. Our results provide new tools on BP analysis and new directions on efficient solvers for large-scale LPs.

Connected through hyperedge HE-1 (induced by source paper "optimality of belief propagation for crowdsourced classification"):
  with members:
    - "achieving budget optimality with adaptive schemes in crowdsourcing"
    - "regularized minimax conditional entropy for crowdsourcing"
    - "spectral detection in the censored block model"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "budget optimal task allocation for reliable crowdsourcing systems"
    - "matrix completion from a few entries"

Connected through hyperedge HE-2 (induced by source paper "optimal inference in crowdsourced classification via belief propagation"):
  with members:
    - "optimality of belief propagation for crowdsourced classification"
    - "regularized minimax conditional entropy for crowdsourcing"
    - "spectral detection on sparse hypergraphs"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "budget optimal task allocation for reliable crowdsourcing systems"

Connected through hyperedge HE-3 (induced by source paper "minimum weight perfect matching via blossom belief propagation"):
  with members:
    - "the cutting plane method is polynomial for perfect matchings"
    - "map estimation linear programming and belief propagation with convex free energies"
    - "complexity of inference in graphical models"
    - "belief propagation for weighted b matchings on arbitrary graphs and its relation to linear programs with integer solutions"
    - "belief propagation for min cost network flow convergence and correctness"
    - "message passing for maximum weight independent set"
    - "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.AI(Artificial Intelligence)