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 connected dominating set on graphs with excluded topological subgraphs"
  Abstract: We give the first linear kernels for the (Connected) Dominating Set problems on H-topological minor free graphs. We prove the existence of polynomial time algorithms that, for a given H-topological-minor-free graph G and a positive integer k, output an H-topological-minor-free graph G' on O(k) vertices such that G has a (connected) dominating set of size k iff G' has one. Our results extend the known classes of graphs on which the Dominating Set and Connected Dominating Set problems admit linear kernels. Prior to our work, it was known that these problems admit linear kernels on graphs excluding a fixed apex graph H as a minor. Moreover, for Dominating Set, a kernel of size kc(H), where c(H) is a constant depending on the size of H, follows from a more general result on the kernelization of Dominating Set on graphs of bounded degeneracy. Alon and Gutner explicitly asked whether one can obtain a linear kernel for Dominating Set on H-minor-free graphs. We answer this question in the affirmative and in fact prove a more general result. For Connected Dominating Set no polynomial kernel even on H-minor-free graphs was known prior to our work. On the negative side, it is known that Connected Dominating Set on 2-degenerated graphs does not admit a polynomial kernel unless coNP $\subseteq$ NP/poly. Our kernelization algorithm is based on a non-trivial combination of the following ingredients The structural theorem of Grohe and Marx [STOC 2012] for graphs excluding a fixed graph H as a topological minor; A novel notion of protrusions, different than the one defined in [FOCS 2009]; Our results are based on a generic reduction rule that produces an equivalent instance (in case the input graph is H-minor-free) of the problem, with treewidth $O(\sqrt{k})$. The application of this rule in a divide-and-conquer fashion, together with the new notion of protrusions, gives us the linear kernels.

Connected through hyperedge HE-1 (induced by source paper "a general kernelization technique for domination and independence problems in sparse classes"):
  with members:
    - "kernelization and approximation of distance r independent sets on nowhere dense graphs"
    - "the generalised colouring numbers on classes of bounded expansion"
    - "characterising bounded expansion by neighbourhood complexity"
    - "polynomial kernels and wideness properties of nowhere dense graph classes"
    - "bidimensionality and kernels"
    - "polynomial time data reduction for dominating set"

Connected through hyperedge HE-2 (induced by source paper "lossy kernels for connected dominating set on sparse graphs"):
  with members:
    - "from gap eth to fpt inapproximability clique dominating set and more"
    - "on the number of types in sparse graphs"
    - "the generalised colouring numbers on classes of bounded expansion"
    - "characterising bounded expansion by neighbourhood complexity"
    - "polynomial kernels and wideness properties of nowhere dense graph classes"
    - "bidimensionality and kernels"
    - "neighborhood complexity and kernelization for nowhere dense classes of graphs"
    - "approximation algorithms for polynomial expansion and low density graphs"

Connected through hyperedge HE-3 (induced by source paper "characterising bounded expansion by neighbourhood complexity"):
  with members:
    - "bidimensionality and kernels"
    - "structural sparsity of complex networks bounded expansion in random models and real world graphs"
    - "kernelization and sparseness the case of dominating set"
    - "kernelization using structural parameters on sparse graph classes"
    - "deciding first order properties of nowhere dense graphs"
    - "linear kernels and single exponential algorithms via protrusion decompositions"
    - "structure theorem and isomorphism test for graphs with excluded topological subgraphs"
    - "homomorphism preservation on quasi wide classes"

Connected through hyperedge HE-4 (induced by source paper "bidimensionality and kernels"):
  with members:
    - "improved bounds for the excluded grid theorem"
    - "linear kernels for edge deletion problems to immersion closed graph classes"
    - "neighborhood complexity and kernelization for nowhere dense classes of graphs"
    - "kernelization and sparseness the case of dominating set"
    - "explicit linear kernels via dynamic programming"
    - "bidimensionality of geometric intersection graphs"
    - "polynomial bounds for the grid minor theorem"
    - "linear kernels and single exponential algorithms via protrusion decompositions"

Connected through hyperedge HE-5 (induced by source paper "polynomial kernels and wideness properties of nowhere dense graph classes"):
  with members:
    - "bidimensionality and kernels"
    - "neighborhood complexity and kernelization for nowhere dense classes of graphs"
    - "kernelization and sparseness the case of dominating set"
    - "kernelization using structural parameters on sparse graph classes"
    - "deciding first order properties of nowhere dense graphs"
    - "structure theorem and isomorphism test for graphs with excluded topological subgraphs"
    - "homomorphism preservation on quasi wide classes"
    - "polynomial time data reduction for dominating set"

Connected through hyperedge HE-6 (induced by source paper "neighborhood complexity and kernelization for nowhere dense classes of graphs"):
  with members:
    - "the generalised colouring numbers on classes of bounded expansion"
    - "characterising bounded expansion by neighbourhood complexity"
    - "polynomial kernels and wideness properties of nowhere dense graph classes"
    - "bidimensionality and kernels"
    - "kernelization and sparseness the case of dominating set"
    - "homomorphism preservation on quasi wide classes"
    - "polynomial time data reduction for dominating set"

Connected through hyperedge HE-7 (induced by source paper "on kernelization and approximation for the vector connectivity problem"):
  with members:
    - "bidimensionality and kernels"
    - "on the complexity of the vector connectivity problem"
    - "kernelization lower bounds by cross composition"
    - "designing fpt algorithms for cut problems using randomized contractions"
    - "linear kernels and single exponential algorithms via protrusion decompositions"
    - "representative sets and irrelevant vertices new tools for kernelization"
    - "finding small separators in linear time via treewidth reduction"

Connected through hyperedge HE-8 (induced by source paper "a linear kernel for planar red blue dominating set"):
  with members:
    - "bidimensionality and kernels"
    - "explicit linear kernels via dynamic programming"
    - "linear kernels and single exponential algorithms via protrusion decompositions"
    - "a linear kernel for planar total dominating set"
    - "polynomial time data reduction for dominating set"

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)