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: "optimal data reduction for graph coloring using low degree polynomials"
  Abstract: The theory of kernelization can be used to rigorously analyze data reduction for graph coloring problems. Here, the aim is to reduce a q-Coloring input to an equivalent but smaller input whose size is provably bounded in terms of structural properties, such as the size of a minimum vertex cover. In this paper we settle two open problems about data reduction for q-Coloring. #R##N#First, we obtain a kernel of bitsize $O(k^{q-1}\log{k})$ for q-Coloring parameterized by Vertex Cover, for any q >= 3. This size bound is optimal up to $k^{o(1)}$ factors assuming NP is not a subset of coNP/poly, and improves on the previous-best kernel of size $O(k^q)$. We generalize this result for deciding q-colorability of a graph G, to deciding the existence of a homomorphism from G to an arbitrary fixed graph H. Furthermore, we can replace the parameter vertex cover by the less restrictive parameter twin-cover. We prove that H-Coloring parameterized by Twin-Cover has a kernel of size $O(k^{\Delta(H)}\log k)$. #R##N#Our second result shows that 3-Coloring does not admit non-trivial sparsification: assuming NP is not a subset of coNP/poly, the parameterization by the number of vertices n admits no (generalized) kernel of size $O(n^{2-e})$ for any e > 0. Previously, such a lower bound was only known for coloring with q >= 4 colors.

Connected through hyperedge HE-1 (induced by source paper "parameterized complexity of conflict free graph coloring"):
  with members:
    - "optimal sparsification for some binary csps using low degree polynomials"
    - "data reduction for graph coloring problems"
    - "kernelization lower bounds by cross composition"
    - "known algorithms on graphs of bounded treewidth are probably optimal"

Connected through hyperedge HE-2 (induced by source paper "best case and worst case sparsifiability of boolean csps"):
  with members:
    - "which np hard sat and csp problems admit exponentially improved algorithms"
    - "kernelization of constraint satisfaction problems a study through universal algebra"
    - "optimal sparsification for some binary csps using low degree polynomials"
    - "sparsification upper and lower bounds for graph problems and not all equal sat"
    - "point line cover the easy kernel is essentially tight"
    - "on sparsification for computing treewidth"
    - "weak bases of boolean co clones"
    - "kernelization lower bounds by cross composition"

Connected through hyperedge HE-3 (induced by source paper "optimal sparsification for some binary csps using low degree polynomials"):
  with members:
    - "best case and worst case sparsifiability of boolean csps"
    - "kernelization of constraint satisfaction problems a study through universal algebra"
    - "complexity and approximability of parameterized max csps"
    - "sparsification upper and lower bounds for graph problems and not all equal sat"
    - "nonclassical polynomials as a barrier to polynomial lower bounds"
    - "on sparsification for computing treewidth"
    - "kernelization lower bounds by cross composition"
    - "constraint satisfaction parameterized by solution size"

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)