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: "kernelization lower bounds by cross composition"
  Abstract: We introduce the cross-composition framework for proving kernelization lower bounds. A classical problem L AND/OR-cross-composes into a parameterized problem Q if it is possible to efficiently construct an instance of Q with polynomially bounded parameter value that expresses the logical AND or 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) with a refinement by Dell and van Melkebeek (STOC 2010), we show that if an NP-hard problem OR-cross-composes into a parameterized problem Q then Q does not admit a polynomial kernel unless NP \subseteq coNP/poly and the polynomial hierarchy collapses. Similarly, an AND-cross-composition for Q rules out polynomial kernels for Q under Bodlaender et al.'s AND-distillation conjecture. #R##N#Our technique generalizes and strengthens the recent techniques of using 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., Clique, Chromatic Number, Weighted Feedback Vertex Set, and Weighted Odd Cycle Transversal 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. #R##N#After learning of our results, several teams of authors have successfully applied the cross-composition framework to different parameterized problems. For completeness, our presentation of the framework includes several extensions based on this follow-up work. For example, we show how a relaxed version of OR-cross-compositions may be used to give lower bounds on the degree of the polynomial in the kernel size.

Connected through hyperedge HE-1 (induced by source paper "subexponential parameterized algorithms and kernelization on almost chordal graphs"):
  with members:
    - "a complexity dichotomy for hitting connected minors on bounded treewidth graphs the chair and the banner draw the boundary"
    - "feedback vertex set inspired kernel for chordal vertex deletion"
    - "approximation and kernelization for chordal vertex deletion"
    - "polynomial kernels for weighted problems"
    - "linear recognition of almost interval graphs"
    - "large induced subgraphs via triangulations and cmso"
    - "data reduction for graph coloring problems"
    - "interval deletion is fixed parameter tractable"

Connected through hyperedge HE-2 (induced by source paper "parameterized algorithms and data reduction for the short secluded s t path problem"):
  with members:
    - "on the computational complexity of length and neighborhood constrained path problems"
    - "the parameterized complexity of finding secluded solutions to some classical optimization problems on graphs"
    - "a parameterized approximation algorithm for the mixed and windy capacitated arc routing problem theory and experiments"
    - "finding connected secluded subgraphs"
    - "polynomial kernels for weighted problems"
    - "parameterized complexity of secluded connectivity problems"
    - "route planning in transportation networks"
    - "parameterized complexity of the k arc chinese postman problem"

Connected through hyperedge HE-3 (induced by source paper "the computational complexity of finding temporal paths under waiting time constraints"):
  with members:
    - "an adaptive version of brandes algorithm for betweenness centrality"
    - "efficient computation of optimal temporal walks under waiting time constraints"
    - "how fast can we reach a target vertex in stochastic temporal graphs"
    - "temporal cliques admit sparse spanners"
    - "fixed parameter algorithms for maximum profit facility location under matroid constraints"
    - "the temporal explorer who returns to the base"
    - "changing times to minimise reachability in temporal graphs"
    - "deleting edges to restrict the size of an epidemic in temporal networks"

Connected through hyperedge HE-4 (induced by source paper "computing maximum matchings in temporal graphs"):
  with members:
    - "temporal matching"
    - "how fast can we reach a target vertex in stochastic temporal graphs"
    - "fixed parameter algorithms for maximum profit facility location under matroid constraints"
    - "tight competitive ratios of classic matching algorithms in the fully online model"
    - "temporal vertex cover with a sliding time window"
    - "how to match when all vertices arrive online"
    - "sliding window temporal graph coloring"
    - "efficient and adaptive parameterized algorithms on modular decompositions"

Connected through hyperedge HE-5 (induced by source paper "on the approximate compressibility of connected vertex cover"):
  with members:
    - "revisiting connected vertex cover fpt algorithms and lossy kernels"
    - "smaller parameters for vertex cover kernelization"
    - "approximation and kernelization for chordal vertex deletion"
    - "how much does a treedepth modulator help to obtain polynomial kernels beyond sparse graphs"
    - "a randomized polynomial kernelization for vertex cover with a smaller parameter"
    - "vertex cover structural parameterization revisited"
    - "kernelization of packing problems"
    - "representative sets and irrelevant vertices new tools for kernelization"

Connected through hyperedge HE-6 (induced by source paper "elimination distances blocking sets and kernels for vertex cover"):
  with members:
    - "polynomial kernels for hitting forbidden minors under structural parameterizations"
    - "smaller parameters for vertex cover kernelization"
    - "a randomized polynomial kernelization for vertex cover with a smaller parameter"
    - "vertex cover structural parameterization revisited"
    - "raising the bar for vertex cover fixed parameter tractability above a higher guarantee"
    - "graph isomorphism parameterized by elimination distance to bounded degree"
    - "representative sets and irrelevant vertices new tools for kernelization"
    - "vertex cover kernelization revisited upper and lower bounds for a refined parameter"

Connected through hyperedge HE-7 (induced by source paper "on kernelization for edge dominating set under structural parameters"):
  with members:
    - "a randomized polynomial kernelization for vertex cover with a smaller parameter"
    - "raising the bar for vertex cover fixed parameter tractability above a higher guarantee"
    - "polynomial delay algorithm for listing minimal edge dominating sets in graphs"
    - "faster parameterized algorithms using linear programming"
    - "kernelization of packing problems"
    - "representative sets and irrelevant vertices new tools for kernelization"
    - "on multiway cut parameterized above lower bounds"
    - "vertex cover kernelization revisited upper and lower bounds for a refined parameter"

Connected through hyperedge HE-8 (induced by source paper "the parameterized complexity of motion planning for snake like robots"):
  with members:
    - "towards tight er bounds for the excluded grid theorem"
    - "coordinated motion planning reconfiguring a swarm of labeled robots with bounded stretch"
    - "push pull block puzzles are hard"
    - "how to navigate through obstacles"
    - "a survey of motion planning and control techniques for self driving urban vehicles"
    - "polynomial bounds for the grid minor theorem"

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)