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: "impossibility of independence amplification in kolmogorov complexity theory"
  Abstract: The paper studies randomness extraction from sources with bounded independence and the issue of independence amplification of sources, using the framework of Kolmogorov complexity. The dependency of strings x and y is dep(x, y) = max{C(x) - C(x | y), C(y) - C(y | x)}, where C(ċ) denotes the Kolmogorov complexity. It is shown that there exists a computable Kolmogorov extractor f such that, for any two n-bit strings with complexity s(n) and dependency α(n), it outputs a string of length s(n) with complexity s(n) - α(n) conditioned by any one of the input strings. It is proven that the above are the optimal parameters a Kolmogorov extractor can achieve. It is shown that independence amplification cannot be effectively realized. Specifically, if (after excluding a trivial case) there exist computable functions f1 and f2 such that dep(f1(x, y), f2(x, y)) ≤ β(n) for all n-bit strings x and y with dep(x, y) ≤ α(n), then β(n) ≥ α(n) - O(log n).

Connected through hyperedge HE-1 (induced by source paper "space bounded kolmogorov extractors"):
  with members:
    - "possibilities and impossibilities in kolmogorov complexity extraction"
    - "symmetry of information and bounds on nonuniform randomness extraction via kolmogorov extractors"
    - "on the optimal compression of sets in pspace"
    - "pseudo random graphs and bit probe schemes with one sided error"
    - "improving the space bounded version of muchnik s conditional complexity theorem via naive derandomization"
    - "extracting the kolmogorov complexity of strings and sequences from sources with limited independence"
    - "two sources are better than one for increasing the kolmogorov complexity of infinite sequences"

Connected through hyperedge HE-2 (induced by source paper "possibilities and impossibilities in kolmogorov complexity extraction"):
  with members:
    - "counting dependent and independent strings"
    - "extracting the kolmogorov complexity of strings and sequences from sources with limited independence"
    - "algorithmically independent sequences"
    - "two sources are better than one for increasing the kolmogorov complexity of infinite sequences"
    - "constructive dimension and turing degrees"
    - "dimension extractors and optimal decompression"

Connected through hyperedge HE-3 (induced by source paper "improving the space bounded version of muchnik s conditional complexity theorem via naive derandomization"):
  with members:
    - "space bounded kolmogorov extractors"
    - "symmetry of information and bounds on nonuniform randomness extraction via kolmogorov extractors"
    - "on the optimal compression of sets in pspace"
    - "pseudo random graphs and bit probe schemes with one sided error"
    - "extracting the kolmogorov complexity of strings and sequences from sources with limited independence"
    - "variations on muchnik s conditional complexity theorem"

Connected through hyperedge HE-4 (induced by source paper "counting dependent and independent strings"):
  with members:
    - "possibilities and impossibilities in kolmogorov complexity extraction"
    - "extracting the kolmogorov complexity of strings and sequences from sources with limited independence"
    - "on generating independent random strings"
    - "two sources are better than one for increasing the kolmogorov complexity of infinite sequences"

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)