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: "cross composition a new technique for kernelization lower bounds"
  Abstract: We introduce a new technique for proving kernelization lower bounds, called cross-composition. A classical problem L cross-composes into a parameterized problem Q if an instance of Q with polynomially bounded parameter value can express the logical OR of a sequence of instances of L. Building on work by Bodlaender et al. (ICALP 2008) and using a result by Fortnow and Santhanam (STOC 2008) we show that if an NP-complete problem cross-composes into a parameterized problem Q then Q does not admit a polynomial kernel unless the polynomial hierarchy collapses. Our technique generalizes and strengthens the recent techniques of using OR-composition algorithms and of transferring the lower bounds via polynomial parameter transformations. We show its applicability by proving kernelization lower bounds for a number of important graphs problems with structural (non-standard) parameterizations, e.g., Chromatic Number, Clique, and Weighted Feedback Vertex Set do not admit polynomial kernels with respect to the vertex cover number of the input graphs unless the polynomial hierarchy collapses, contrasting the fact that these problems are trivially fixed-parameter tractable for this parameter. We have similar lower bounds for Feedback Vertex Set.

Connected through hyperedge HE-1 (induced by source paper "parameterized coloring problems on threshold graphs"):
  with members:
    - "between treewidth and clique width"
    - "data reduction for graph coloring problems"
    - "algorithms and almost tight results for 3 colorability of small diameter graphs"

Connected through hyperedge HE-2 (induced by source paper "fixing improper colorings of graphs"):
  with members:
    - "optimal parameterized algorithms for planar facility location problems using voronoi diagrams"
    - "recoloring bounded treewidth graphs"
    - "known algorithms on graphs of bounded treewidth are probably optimal"

Connected through hyperedge HE-3 (induced by source paper "on the parameterized complexity of computing balanced partitions in graphs"):
  with members:
    - "expanding the expressive power of monadic second order logic on restricted graph classes"
    - "minimum bisection is fixed parameter tractable"
    - "kernelization lower bounds by cross composition"
    - "fast balanced partitioning is hard even on grids and trees"
    - "finding small separators in linear time via treewidth reduction"
    - "treewidth reduction for constrained separation and bipartization problems"

Connected through hyperedge HE-4 (induced by source paper "interval scheduling and colorful independent sets"):
  with members:
    - "kernelization lower bounds by cross composition"
    - "parameterizing by the number of numbers"

Connected through hyperedge HE-5 (induced by source paper "on the complexity of various parameterizations of common induced subgraph isomorphism"):
  with members:
    - "slightly superexponential parameterized problems"
    - "deciding first order properties of nowhere dense graphs"
    - "kernelization lower bounds by cross composition"
    - "cleaning interval graphs"
    - "known algorithms on graphs of bounded treewidth are probably optimal"
    - "linear time algorithms for finding a dominating set of fixed size in degenerated graphs"
    - "fixed parameter tractability definability and model checking"

Connected through hyperedge HE-6 (induced by source paper "win win kernelization for degree sequence completion problems"):
  with members:
    - "improved upper and lower bound heuristics for degree anonymization in social networks"
    - "editing to a connected graph of given degrees"
    - "editing to a graph of given degrees"
    - "kernelization lower bounds by cross composition"
    - "the h index of a graph and its application to dynamic subgraph statistics"
    - "a generalization of nemhauser and trotter s local optimization theorem"

Connected through hyperedge HE-7 (induced by source paper "kernelization lower bound for permutation pattern matching"):
  with members:
    - "finding small patterns in permutations in linear time"
    - "the computational landscape of permutation patterns"
    - "a fast algorithm for permutation pattern matching based on alternating runs"

Connected through hyperedge HE-8 (induced by source paper "explicit linear kernels via dynamic programming"):
  with members:
    - "slightly superexponential parameterized problems"
    - "bidimensionality and kernels"
    - "uniform kernelization complexity of hitting forbidden minors"
    - "large treewidth graph decompositions and applications"
    - "polynomial bounds for the grid minor theorem"
    - "linear kernels and single exponential algorithms via protrusion decompositions"
    - "bidimensionality and eptas"
    - "known algorithms on graphs of bounded treewidth are probably optimal"

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)