human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "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.

Includes members:
  Member "data reduction for graph coloring problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "subexponential parameterized algorithms and kernelization on almost chordal graphs")
  Member "kernelization of packing problems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the approximate compressibility of connected vertex cover")
  Member "representative sets and irrelevant vertices new tools for kernelization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on quasipolynomial multicut mimicking networks and kernelization of multiway cut problems")
  Member "kernel bounds for path and cycle problems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "parameterized pre coloring extension and list coloring problems")
  Member "clique cover and graph separation new incompressibility results":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "clustering to given connectivities")
  Member "preprocessing for treewidth a combinatorial analysis through kernelization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "measuring what matters a hybrid approach to dynamic programming with treewidth")
  Member "on polynomial kernels for structural parameterizations of odd cycle transversal":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "characterizing the easy to find subgraphs from the viewpoint of polynomial time algorithms kernels and turing kernels")
  Member "co nondeterminism in compositions a kernelization lower bound for a ramsey type problem":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "frameworks for solving turing kernel lower bound problem and finding natural candidate problems in np intermediate")

Question: Please tell me which class the source paper 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)