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: "co nondeterminism in compositions a kernelization lower bound for a ramsey type problem"
  Abstract: Until recently, techniques for obtaining lower bounds for kernelization were one of the most sought after tools in the field of parameterized complexity. Now, after a strong influx of techniques, we are in the fortunate situation of having tools available that are even stronger than what has been required in their applications so far. Based on a result of Fortnow and Santhanam (JCSS 2011), Bodlaender et al. (JCSS 2009) showed that, unless NP \subseteq coNP/poly, the existence of a deterministic polynomial-time composition algorithm, i.e., an algorithm which outputs an instance of bounded parameter value which is yes if and only if one of t input instances is yes, rules out the existence of polynomial kernels for a problem. Dell and van Melkebeek (STOC 2010) continued this line of research and, amongst others, were able to rule out kernels of size O(k^d-eps) for certain problems, assuming NP !\subseteq coNP/poly. Their work implies that even the existence of a co-nondeterministic composition rules out polynomial kernels. #R##N#In this work we present the first example of how co-nondeterminism can help to make a composition algorithm. We study a Ramsey-type problem: Given a graph G and an integer k, the question is whether G contains an independent set or a clique of size at least k. It was asked by Rod Downey whether this problem admits a polynomial kernelization. We provide a co-nondeterministic composition based on embedding t instances into a single host graph H. The crux is that the host graph H needs to observe a bound of L \in O(log t) on both its maximum independent set and maximum clique size, while also having a cover of its vertex set by independent sets and cliques all of size L; the co-nondeterministic composition is build around the search for such graphs. Thus we show that, unless NP \subseteq coNP/poly, the problem does not admit a kernelization with polynomial size guarantee.

Connected through hyperedge HE-1 (induced by source paper "frameworks for solving turing kernel lower bound problem and finding natural candidate problems in np intermediate"):
  with members:
    - "turing kernelization for finding long paths and cycles in restricted graph classes"
    - "abusing the tutte matrix an algebraic instance compression for the k set cycle problem"
    - "point line cover the easy kernel is essentially tight"
    - "kernelization lower bounds by cross composition"
    - "non existence of polynomial kernels for the test cover problem"
    - "kernelization of packing problems"
    - "clique cover and graph separation new incompressibility results"
    - "vertex cover kernelization revisited upper and lower bounds for a refined parameter"

Connected through hyperedge HE-2 (induced by source paper "and compression of np complete problems streamlined proof and minor observations"):
  with members:
    - "point line cover the easy kernel is essentially tight"
    - "kernelization lower bounds by cross composition"
    - "kernelization of packing problems"
    - "generalised pinsker inequalities"

Connected through hyperedge HE-3 (induced by source paper "sparsification upper and lower bounds for graph problems and not all equal sat"):
  with members:
    - "optimal sparsification for some binary csps using low degree polynomials"
    - "tight kernel bounds for problems on graphs with small degeneracy"
    - "data reduction for graph coloring problems"
    - "on sparsification for computing treewidth"
    - "kernelization lower bounds by cross composition"
    - "kernelization of packing problems"
    - "kernel bounds for path and cycle problems"
    - "dominating set is fixed parameter tractable in claw free graphs"

Connected through hyperedge HE-4 (induced by source paper "characterizing the easy to find subgraphs from the viewpoint of polynomial time algorithms kernels and turing kernels"):
  with members:
    - "turing kernelization for finding long paths and cycles in restricted graph classes"
    - "a polynomial turing kernel for weighted independent set in bull free graphs"
    - "the parameterized complexity of k biclique"
    - "everything you always wanted to know about the parameterized complexity of subgraph isomorphism but were afraid to ask"
    - "data reduction for graph coloring problems"
    - "kernelization lower bounds by cross composition"
    - "kernelization of packing problems"
    - "kernel bounds for path and cycle problems"

Connected through hyperedge HE-5 (induced by source paper "tight kernel bounds for problems on graphs with small degeneracy"):
  with members:
    - "bidimensionality and kernels"
    - "kernelization lower bounds by cross composition"
    - "linear kernels and single exponential algorithms via protrusion decompositions"
    - "linear kernels on graphs excluding topological minors"
    - "kernelization of packing problems"
    - "cross composition a new technique for kernelization lower bounds"
    - "polynomial time data reduction for dominating set"

Connected through hyperedge HE-6 (induced by source paper "fpt is characterized by useful obstruction sets"):
  with members:
    - "data reduction for graph coloring problems"
    - "cross composition a new technique for kernelization lower bounds"

Connected through hyperedge HE-7 (induced by source paper "point line cover the easy kernel is essentially tight"):
  with members:
    - "tight kernel bounds for problems on graphs with small degeneracy"
    - "kernelization of packing problems"

Connected through hyperedge HE-8 (induced by source paper "kernelization lower bounds by cross composition"):
  with members:
    - "data reduction for graph coloring problems"
    - "kernelization of packing problems"
    - "representative sets and irrelevant vertices new tools for kernelization"
    - "kernel bounds for path and cycle problems"
    - "clique cover and graph separation new incompressibility results"
    - "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"

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)