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: "quantifier elimination for statistical problems"
  Abstract: Recent improvement on Tarski's procedure for quantifier elimination in the first order theory of real numbers makes it feasible to solve small instances of the following problems completely automatically: 1. listing all equality and inequality constraints implied by a graphical model with hidden variables. 2. Comparing graphyical models with hidden variables (i.e., model equivalence, inclusion, and overlap). 3. Answering questions about the identification of a model or portion of a model, and about bounds on quantities derived from a model. 4. Determing whether a given set of independence assertions. We discuss the foundation of quantifier elimination and demonstrate its application to these problems.

Connected through hyperedge HE-1 (induced by source paper "inequality constraints in causal models with hidden variables"):
  with members:
    - "counterfactual probabilities computational methods bounds and applications"
    - "graphical models and exponential families"
    - "on the testability of causal models with latent and instrumental variables"
    - "causal discovery from a mixture of experimental and observational data"
    - "instrumentality tests revisited"
    - "a bayesian approach to learning causal networks"
    - "on the testable implications of causal models with hidden variables"
    - "decision theoretic foundations for causal reasoning"

Connected through hyperedge HE-2 (induced by source paper "statistical tests for contagion in observational social network studies"):
  with members:
    - "inequality constraints in causal models with hidden variables"
    - "social contagion theory examining dynamic social networks and human behavior"
    - "a sequence of relaxations constraining hidden variable models"

Connected through hyperedge HE-3 (induced by source paper "a sequence of relaxations constraining hidden variable models"):
  with members:
    - "graphical models and exponential families"
    - "instrumentality tests revisited"
    - "inequality constraints in causal models with hidden variables"
    - "polynomial constraints in causal bayesian networks"
    - "on the testable implications of causal models with hidden variables"
    - "information contagion an empirical study of the spread of news on digg and twitter social networks"

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)