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: "inequality constraints in causal models with hidden variables"
  Abstract: We present a class of inequality constraints on the set of distributions induced by local interventions on variables governed by a causal Bayesian network, in which some of the variables remain unmeasured. We derive bounds on causal effects that are not directly measured in randomized experiments. We derive instrumental inequality type of constraints on nonexperimental distributions. The results have applications in testing causal models with observational or experimental data.

Connected through hyperedge HE-1 (induced by source paper "learning and testing causal models with interventions"):
  with members:
    - "learning graphical models using multiplicative weights"
    - "a new approach for testing properties of discrete distributions"
    - "testing ising models"
    - "square hellinger subadditivity for bayesian networks and its applications to identity testing"
    - "testing bayesian networks"
    - "optimal testing for properties of distributions"
    - "an algorithm for deciding if a set of observed independencies has a causal explanation"
    - "causal networks semantics and expressiveness"

Connected through hyperedge HE-2 (induced by source paper "polynomial constraints in causal bayesian networks"):
  with members:
    - "graphical models and exponential families"
    - "on the testable implications of causal models with hidden variables"
    - "decision theoretic foundations for causal reasoning"

Connected through hyperedge HE-3 (induced by source paper "statistical tests for contagion in observational social network studies"):
  with members:
    - "quantifier elimination for statistical problems"
    - "social contagion theory examining dynamic social networks and human behavior"
    - "a sequence of relaxations constraining hidden variable models"

Connected through hyperedge HE-4 (induced by source paper "a sequence of relaxations constraining hidden variable models"):
  with members:
    - "quantifier elimination for statistical problems"
    - "graphical models and exponential families"
    - "instrumentality tests revisited"
    - "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)