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 "hybrid influence diagrams using mixtures of truncated exponentials"):
  Abstract: Mixtures of truncated exponentials (MTE) potentials are an alternative to discretization for representing continuous chance variables in influence diagrams. Also, MTE potentials can be used to approximate utility functions. This paper introduces MTE influence diagrams, which can represent decision problems without restrictions on the relationships between continuous and discrete chance variables, without limitations on the distributions of continuous chance variables, and without limitations on the nature of the utility functions. In MTE influence diagrams, all probability distributions and the joint utility function (or its multiplicative factors) are represented by MTE potentials and decision nodes are assumed to have discrete state spaces. MTE influence diagrams are solved by variable elimination using a fusion algorithm.

Includes members:
  Member "solving influence diagrams using hugin shafer shenoy and lazy propagation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "solving limited memory influence diagrams using branch and bound search")
  Member "from influence diagrams to junction trees":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a symbolic algebra for the computation of expected utilities in multiplicative influence diagrams")
  Member "mixtures of gaussians and minimum relative entropy techniques for modeling continuous uncertainties":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "laplace s method approximations for probabilistic inference in belief networks with continuous variables")
  Member "lazy evaluation of symmetric bayesian decision problems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "representing and solving asymmetric bayesian decision problems")
  Member "using potential influence diagrams for probabilistic inference and decision making":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "myopic value of information in influence diagrams")

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)