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 "list approximation for increasing kolmogorov complexity"):
  Abstract: It is impossible to effectively modify a string in order to increase its Kolmogorov complexity. But is it possible to construct a few strings, not longer than the input string, so that most of them have larger complexity? We show that the answer is yes. We present an algorithm that on input a string $x$ of length $n$ returns a list with $O(n^2)$ many strings, all of length $n$, such that 99\% of them are more complex than $x$, provided the complexity of $x$ is less than $n - \log \log n - O(1)$. We obtain similar results for other parameters, including a polynomial-time construction.

Includes members:
  Member "kolmogorov complexity version of slepian wolf coding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "universal almost optimal compression and slepian wolf coding in probabilistic polynomial time")
  Member "short lists with short programs in short time":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "how incomputable is kolmogorov complexity")
  Member "short lists with short programs in short time a short proof":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "how incomputable is kolmogorov complexity")
  Member "linear list approximation for short programs or the power of a few random bits":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "universal almost optimal compression and slepian wolf coding in probabilistic polynomial time")
  Member "short lists for shortest descriptions in short time":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "universal almost optimal compression and slepian wolf coding in probabilistic polynomial time")

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)