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: "all sampling methods produce outliers"
  Abstract: Given a computable probability measure P over natural numbers or infinite binary sequences, there is no computable, randomized method that can produce an arbitrarily large sample such that none of its members are outliers of P.

Connected through hyperedge HE-1 (induced by source paper "approximations of kolmogorov complexity"):
  with members:
    - "on the complexity of completing binary predicates"
    - "list approximation for increasing kolmogorov complexity"
    - "algorithmic statistics forty years later"
    - "short lists with short programs in short time"

Connected through hyperedge HE-2 (induced by source paper "information kernels"):
  with members:
    - "algorithmic statistics forty years later"
    - "algorithmic statistics revisited"
    - "rate distortion and denoising of individual data using kolmogorov complexity"
    - "kolmogorov s structure functions and model selection"

Connected through hyperedge HE-3 (induced by source paper "on the algorithmic probability of sets"):
  with members:
    - "algorithmic statistics forty years later"
    - "algorithmic statistics revisited"
    - "kolmogorov s structure functions and model selection"

Connected through hyperedge HE-4 (induced by source paper "on the complexity of completing binary predicates"):
  with members:
    - "algorithmic statistics forty years later"
    - "algorithmic statistics revisited"
    - "kolmogorov s structure functions and model selection"

Connected through hyperedge HE-5 (induced by source paper "on quantum noncompression"):
  with members:
    - "an information theoretic representation of agent dynamics as set intersections"
    - "sets have simple members"
    - "algorithmic rate distortion theory"
    - "rate distortion and denoising of individual data using kolmogorov complexity"
    - "kolmogorov s structure functions and model selection"

Connected through hyperedge HE-6 (induced by source paper "quantum coding theorems"):
  with members:
    - "an information theoretic representation of agent dynamics as set intersections"
    - "sets have simple members"
    - "rate distortion and denoising of individual data using kolmogorov complexity"
    - "kolmogorov s structure functions and model selection"

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)