human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "non minimal triangulations for mixed stochastic deterministic graphical models"):
  Abstract: We observe that certain large-clique graph triangulations can be useful to reduce both computational and space requirements when making queries on mixed stochastic/deterministic graphical models. We demonstrate that many of these large-clique triangulations are non-minimal and are thus unattainable via the variable elimination algorithm. We introduce ancestral pairs as the basis for novel triangulation heuristics and prove that no more than the addition of edges between ancestral pairs need be considered when searching for state space optimal triangulations in such graphs. Empirical results on random and real world graphs show that the resulting triangulations that yield significant speedups are almost always non-minimal. We also give an algorithm and correctness proof for determining if a triangulation can be obtained via elimination, and we show that the decision problem associated with finding optimal state space triangulations in this mixed stochastic/deterministic setting is NP-complete.

Includes members:
  Member "approximations in bayesian belief universe for knowledge based systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a tutorial on learning with bayesian networks")
  Member "optimal decomposition of belief networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "potential maximal cliques parameterized by edge clique cover")
  Member "optimal junction trees":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "learning the relation between code features and code transforms with structured prediction")
  Member "pre processing for triangulation of probabilistic networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a complete anytime algorithm for treewidth")
  Member "bucket elimination a unifying framework for several probabilistic inference":
    also connected through other hyperedges:
      (none)
  Member "hybrid processing of beliefs and constraints":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "message passing and combinatorial optimization")
  Member "on triangulating dynamic graphical models":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "graph cuts with interacting edge costs examples approximations and algorithms")
  Member "value elimination bayesian inference via backtracking search":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the sum product theorem a foundation for learning tractable models")

Question: Please tell me which class the source paper 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)