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 "on coloring resilient graphs"):
  Abstract: We introduce a new notion of resilience for constraint satisfaction problems, with the goal of more precisely determining the boundary between NP-hardness and the existence of efficient algorithms for resilient instances. In particular, we study $r$-resiliently $k$-colorable graphs, which are those $k$-colorable graphs that remain $k$-colorable even after the addition of any $r$ new edges. We prove lower bounds on the NP-hardness of coloring resiliently colorable graphs, and provide an algorithm that colors sufficiently resilient graphs. We also analyze the corresponding notion of resilience for $k$-SAT. This notion of resilience suggests an array of open questions for graph coloring and other combinatorial problems.

Includes members:
  Member "improved hardness of approximating chromatic number":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "improved hardness for h colourings of g colourable graphs")
  Member "anti coordination games and stable graph colorings":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "stabilization time in minority processes")
  Member "data stability in clustering a closer look":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on euclidean k means clustering with alpha center proximity")
  Member "a characterization of b perfect graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a survey on the computational complexity of colouring graphs with forbidden subgraphs")
  Member "center based clustering under perturbation stability":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "analysis of ward s method")
  Member "are stable instances easy":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the unreasonable effectiveness of the greedy algorithm greedy adapts to sharpness")
  Member "conditional hardness for approximate coloring":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the generalized orthogonality dimension of generalized kneser graphs bounds and applications")
  Member "algorithms for coloring quadtrees":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "diamond kite adaptive quadrilateral meshing")

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)