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: "the relationship between and or search and variable elimination"
  Abstract: In this paper we compare search and inference in graphical models through the new framework of AND/OR search. Specifically, we compare Variable Elimination (VE) and memoryintensive AND/OR Search (AO) and place algorithms such as graph-based backjumping and no-good and good learning, as well as Recursive Conditioning [7] and Value Elimination [2] within the AND/OR search framework.

Connected through hyperedge HE-1 (induced by source paper "the sum product theorem a foundation for learning tractable models"):
  with members:
    - "recursive decomposition for nonconvex optimization"
    - "a differential approach to inference in bayesian networks"
    - "value elimination bayesian inference via backtracking search"
    - "algebraic model counting"
    - "sum product networks a new deep architecture"
    - "complexity of inference in graphical models"
    - "solving sat and bayesian inference with backtracking search"
    - "the language of search"

Connected through hyperedge HE-2 (induced by source paper "and or multi valued decision diagrams aomdds for graphical models"):
  with members:
    - "value elimination bayesian inference via backtracking search"
    - "new advances in inference by recursive conditioning"
    - "case factor diagrams for structured probabilistic modeling"
    - "mixtures of deterministic probabilistic networks and their and or search space"
    - "and or multi valued decision diagrams aomdds for weighted graphical models"
    - "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)