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 "topological parameters for time space tradeoff"):
  Abstract: In this paper we propose a family of algorithms combining tree-clustering with conditioning that trade space for time. Such algorithms are useful for reasoning in probabilistic and deterministic networks as well as for accomplishing optimization tasks. By analyzing the problem structure it will be possible to select from a spectrum the algorithm that best meets a given time-space specification.

Includes members:
  Member "graphical models for preference and utility":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "axiomatization of an importance index for k ary games")
  Member "a probabilistic approach to hierarchical model based diagnosis":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "object oriented bayesian networks")
  Member "nested junction trees":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "solving influence diagrams using hugin shafer shenoy and lazy propagation")
  Member "an evaluation of structural parameters for probabilistic reasoning results on benchmark circuits":
    also connected through other hyperedges:
      (none)
  Member "optimal junction trees":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "learning the relation between code features and code transforms with structured prediction")
  Member "global conditioning for probabilistic inference in belief networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "query dags a practical paradigm for implementing belief network inference")
  Member "a sufficiently fast algorithm for finding close to optimal junction trees":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a variational approximation for bayesian networks with discrete and continuous latent variables")

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)