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: "join graph based cost shifting schemes"
  Abstract: We develop several algorithms taking advantage of two common approaches for bounding MPE queries in graphical models: minibucket elimination and message-passing updates for linear programming relaxations. Both methods are quite similar, and offer useful perspectives for the other; our hybrid approaches attempt to balance the advantages of each. We demonstrate the power of our hybrid algorithms through extensive empirical evaluation. Most notably, a Branch and Bound search guided by the heuristic function calculated by one of our new algorithms has recently won first place in the PASCAL2 inference challenge.

Connected through hyperedge HE-1 (induced by source paper "decomposition bounds for marginal map"):
  with members:
    - "message passing algorithms reparameterizations and splittings"
    - "convergent message passing algorithms for inference over general graphs with convex free energies"
    - "map estimation linear programming and belief propagation with convex free energies"
    - "convergent message passing algorithms a unifying view"
    - "tightening lp relaxations for map using message passing"
    - "solving map exactly using systematic search"
    - "a new class of upper bounds on the log partition function"
    - "tightening fractional covering upper bounds on the partition function for high order region graphs"

Connected through hyperedge HE-2 (induced by source paper "variable elimination in the fourier domain"):
  with members:
    - "recursive decomposition for nonconvex optimization"
    - "structured message passing"
    - "a complete anytime algorithm for treewidth"
    - "on the partition function and random maximum a posteriori perturbations"
    - "tightening lp relaxations for map using message passing"
    - "join graph propagation algorithms"
    - "a knowledge compilation map"

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)