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: "kernels for global constraints"
  Abstract: Bessiere et al. (AAAI'08) showed that several intractable global constraints can be efficiently propagated when certain natural problem parameters are small. In particular, the complete propagation of a global constraint is fixed-parameter tractable in k - the number of holes in domains - whenever bound consistency can be enforced in polynomial time; this applies to the global constraints AtMost-NValue and Extended Global Cardinality (EGC). #R##N#In this paper we extend this line of research and introduce the concept of reduction to a problem kernel, a key concept of parameterized complexity, to the field of global constraints. In particular, we show that the consistency problem for AtMost-NValue constraints admits a linear time reduction to an equivalent instance on O(k^2) variables and domain values. This small kernel can be used to speed up the complete propagation of NValue constraints. We contrast this result by showing that the consistency problem for EGC constraints does not admit a reduction to a polynomial problem kernel unless the polynomial hierarchy collapses.

Connected through hyperedge HE-1 (induced by source paper "diversity in combinatorial optimization"):
  with members:
    - "what is known about vertex cover kernelization"
    - "propagation via kernelization the vertex cover constraint"
    - "guarantees and limits of preprocessing in constraint satisfaction and reasoning"
    - "efficient classification for metric data"
    - "parameterized complexity and kernel bounds for hard planning problems"
    - "limits of preprocessing"

Connected through hyperedge HE-2 (induced by source paper "complexity and approximability of parameterized max csps"):
  with members:
    - "solving maxsat and sat on structured cnf formulas"
    - "tractable answer set programming with weight constraints bounded treewidth is not enough"
    - "guarantees and limits of preprocessing in constraint satisfaction and reasoning"
    - "model counting for formulas of bounded clique width"
    - "a characterization of approximation resistance for even k partite csps"
    - "satisfiability of acyclic and almost acyclic cnf formulas"
    - "majority is stablest discrete and sos"
    - "backdoors to acyclic sat"

Connected through hyperedge HE-3 (induced by source paper "propagation via kernelization the vertex cover constraint"):
  with members:
    - "the parameterized complexity of global constraints"

Connected through hyperedge HE-4 (induced by source paper "guarantees and limits of preprocessing in constraint satisfaction and reasoning"):
  with members:
    - "on feedback vertex set new measure and new structures"
    - "parameterized complexity and kernel bounds for hard planning problems"
    - "backdoors to satisfaction"
    - "backdoors to tractable answer set programming"
    - "limits of preprocessing"
    - "range and roots two common patterns for specifying and propagating counting and occurrence constraints"
    - "the parameterized complexity of global constraints"
    - "cutset sampling for bayesian networks"

Connected through hyperedge HE-5 (induced by source paper "constraint satisfaction parameterized by solution size"):
  with members:
    - "on the hardness of losing weight"
    - "the complexity of global cardinality constraints"
    - "preprocessing of min ones problems a dichotomy"

Connected through hyperedge HE-6 (induced by source paper "limits of preprocessing"):
  with members:
    - "backdoors to tractable answer set programming"
    - "range and roots two common patterns for specifying and propagating counting and occurrence constraints"
    - "the parameterized complexity of global constraints"
    - "kernel s for problems with no kernel on out trees with many leaves"
    - "cutset sampling for bayesian networks"
    - "stable models and an alternative logic programming paradigm"

Connected through hyperedge HE-7 (induced by source paper "k gap interval graphs"):
  with members:
    - "data reduction for graph coloring problems"
    - "the parameterized complexity of global constraints"
    - "on restrictions of balanced 2 interval graphs"

Connected through hyperedge HE-8 (induced by source paper "parameterized complexity results for general factors in bipartite graphs with an application to constraint programming"):
  with members:
    - "limits of preprocessing"
    - "the parameterized complexity of global constraints"

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)