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: "hierarchies of inefficient kernelizability"
  Abstract: The framework of Bodlaender et al. (ICALP 2008) and Fortnow and Santhanam (STOC 2008) allows us to exclude the existence of polynomial kernels for a range of problems under reasonable complexity-theoretical assumptions. However, there are also some issues that are not addressed by this framework, including the existence of Turing kernels such as the "kernelization" of Leaf Out Branching(k) into a disjunction over n instances of size poly(k). Observing that Turing kernels are preserved by polynomial parametric transformations, we define a kernelization hardness hierarchy, akin to the M- and W-hierarchy of ordinary parameterized complexity, by the PPT-closure of problems that seem likely to be fundamentally hard for efficient Turing kernelization. We find that several previously considered problems are complete for our fundamental hardness class, including Min Ones d-SAT(k), Binary NDTM Halting(k), Connected Vertex Cover(k), and Clique(k log n), the clique problem parameterized by k log n.

Connected through hyperedge HE-1 (induced by source paper "on polynomial kernels for integer linear programs covering packing and feasibility"):
  with members:
    - "on polynomial kernels for sparse integer linear programs"
    - "reducing a target interval to a few exact queries"
    - "vertex cover kernelization revisited upper and lower bounds for a refined parameter"
    - "cross composition a new technique for kernelization lower bounds"

Connected through hyperedge HE-2 (induced by source paper "preprocessing subgraph and minor problems when does a small vertex cover help"):
  with members:
    - "bidimensionality and kernels"
    - "data reduction for graph coloring problems"
    - "kernel bounds for structural parameterizations of pathwidth"
    - "kernel bounds for path and cycle problems"
    - "preprocessing for treewidth a combinatorial analysis through kernelization"
    - "on polynomial kernels for structural parameterizations of odd cycle transversal"
    - "compression via matroids a randomized polynomial kernel for odd cycle transversal"
    - "vertex cover kernelization revisited upper and lower bounds for a refined parameter"

Connected through hyperedge HE-3 (induced by source paper "kernel bounds for path and cycle problems"):
  with members:
    - "kernelization of packing problems"
    - "narrow sieves for parameterized paths and packings"
    - "determinant sums for undirected hamiltonicity"
    - "cross composition a new technique for kernelization lower bounds"

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.CC(Computational Complexity)