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: "uniform kernelization complexity of hitting forbidden minors"
  Abstract: The F-Minor-Free Deletion problem asks, for a fixed set F and an input consisting of a graph G and integer k, whether k vertices can be removed from G such that the resulting graph does not contain any member of F as a minor. This paper analyzes to what extent provably effective and efficient preprocessing is possible for F-Minor-Free Deletion. Fomin et al. (FOCS 2012) showed that the special case Planar F-Deletion (when F contains at least one planar graph) has a kernel of size f(F) * k^{g(F)} for some functions f and g. The degree g of the polynomial grows very quickly; it is not even known to be computable. Fomin et al. left open whether Planar F-Deletion has kernels whose size is uniformly polynomial, i.e., of the form f(F) * k^c for some universal constant c that does not depend on F. Our results in this paper are twofold. (1) We prove that some Planar F-Deletion problems do not have uniformly polynomial kernels (unless NP is in coNP/poly). In particular, we prove that Treewidth-Eta Deletion does not have a kernel with O(k^{eta/4} - eps) vertices for any eps > 0, unless NP is in coNP/poly. In fact, we even prove the kernelization lower bound for the larger parameter vertex cover number. This resolves an open problem of Cygan et al. (IPEC 2011). It is a natural question whether further restrictions on F lead to uniformly polynomial kernels. However, we prove that even when F contains a path, the degree of the polynomial must, in general, depend on the set F. (2) A canonical F-Minor-Free Deletion problem when F contains a path is Treedepth-eta Deletion: can k vertices be removed to obtain a graph of treedepth at most eta? We prove that Treedepth-eta Deletion admits uniformly polynomial kernels with O(k^6) vertices for every fixed eta. In order to develop the kernelization we prove several new results about the structure of optimal treedepth-decompositions.

Connected through hyperedge HE-1 (induced by source paper "a turing kernelization dichotomy for structural parameterizations of mathcal f minor free deletion"):
  with members:
    - "polynomial kernels for hitting forbidden minors under structural parameterizations"
    - "turing kernelization for finding long paths and cycles in restricted graph classes"
    - "linear time kernelization for feedback vertex set"
    - "data reduction for graph coloring problems"
    - "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-2 (induced by source paper "a deterministic polynomial kernel for odd cycle transversal and vertex multiway cut in planar graphs"):
  with members:
    - "bidimensionality and kernels"
    - "representative sets and irrelevant vertices new tools for kernelization"
    - "compression via matroids a randomized polynomial kernel for odd cycle transversal"
    - "large isolating cuts shrink the multiway cut"
    - "on multiway cut parameterized above lower bounds"
    - "obtaining a planar graph by vertex deletion"

Connected through hyperedge HE-3 (induced by source paper "polynomial kernels for hitting forbidden minors under structural parameterizations"):
  with members:
    - "vertex cover structural parameterization revisited"
    - "a faster parameterized algorithm for treedepth"
    - "one hierarchy spawns another graph deconstructions and the complexity classification of conjunctive queries"

Connected through hyperedge HE-4 (induced by source paper "feedback vertex set inspired kernel for chordal vertex deletion"):
  with members:
    - "polylogarithmic approximation algorithms for weighted mathcal f deletion problems"
    - "turing kernelization for finding long paths and cycles in restricted graph classes"
    - "approximation and kernelization for chordal vertex deletion"
    - "bidimensionality and kernels"
    - "unit interval vertex deletion fewer vertices are relevant"
    - "linear recognition of almost interval graphs"
    - "chordal editing is fixed parameter tractable"
    - "network sparsification for steiner problems on planar and bounded genus graphs"

Connected through hyperedge HE-5 (induced by source paper "approximation and kernelization for chordal vertex deletion"):
  with members:
    - "linear recognition of almost interval graphs"
    - "a subexponential parameterized algorithm for proper interval completion"
    - "kernelization using structural parameters on sparse graph classes"
    - "a polynomial kernel for proper interval vertex deletion"
    - "preprocessing subgraph and minor problems when does a small vertex cover help"
    - "approximation and tidying a problem kernel for s plex cluster vertex deletion"
    - "representative sets and irrelevant vertices new tools for kernelization"
    - "compression via matroids a randomized polynomial kernel for odd cycle transversal"

Connected through hyperedge HE-6 (induced by source paper "a polynomial kernel for distance hereditary vertex deletion"):
  with members:
    - "feedback vertex set inspired kernel for chordal vertex deletion"
    - "approximation and kernelization for chordal vertex deletion"
    - "a single exponential fixed parameter algorithm for distance hereditary vertex deletion"
    - "an fpt algorithm and a polynomial kernel for linear rankwidth 1 vertex deletion"
    - "linear kernels and single exponential algorithms via protrusion decompositions"
    - "split decomposition and graph labelled trees characterizations and fully dynamic algorithms for totally decomposable graphs"

Connected through hyperedge HE-7 (induced by source paper "linear kernels for edge deletion problems to immersion closed graph classes"):
  with members:
    - "bidimensionality and kernels"
    - "polynomial bounds for the grid minor theorem"
    - "planar f deletion approximation and optimal fpt algorithms"
    - "designing fpt algorithms for cut problems using randomized contractions"

Connected through hyperedge HE-8 (induced by source paper "kernelization algorithms for packing problems allowing overlaps"):
  with members:
    - "characterizing the easy to find subgraphs from the viewpoint of polynomial time algorithms kernels and turing kernels"
    - "kernelization algorithms for packing problems allowing overlaps extended version"
    - "kernelization of packing problems"

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.DS(Data Structures and Algorithms)