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 "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.

Includes members:
  Member "smaller parameters for vertex cover kernelization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the approximate compressibility of connected vertex cover")
  Member "fine grained parameterized complexity analysis of graph coloring problems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "new algorithms for mixed dominating set")
  Member "optimal sparsification for some binary csps using low degree polynomials":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "parameterized complexity of conflict free graph coloring")
  Member "how much does a treedepth modulator help to obtain polynomial kernels beyond sparse graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the approximate compressibility of connected vertex cover")
  Member "sparsification upper and lower bounds for graph problems and not all equal sat":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "optimal polynomial time compression for boolean max csp")
  Member "point line cover the easy kernel is essentially tight":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "dynamic complexity meets parameterised algorithms")
  Member "data reduction for graph coloring problems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "subexponential parameterized algorithms and kernelization on almost chordal graphs")
  Member "list h coloring a graph by removing few vertices":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "multi budgeted directed cuts")

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)