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: "short lists for shortest descriptions in short time"
  Abstract: Is it possible to find a shortest description for a binary string? The well-known answer is "no, Kolmogorov complexity is not computable." Faced with this barrier, one might instead seek a short list of candidates which includes a laconic description. Remarkably such approximations exist. This paper presents an efficient algorithm which generates a polynomial-size list containing an optimal description for a given input string. Along the way, we employ expander graphs and randomness dispersers to obtain an Explicit Online Matching Theorem for bipartite graphs and a refinement of Muchnik's Conditional Complexity Theorem. Our main result extends recent work by Bauwens, Mahklin, Vereschchagin, and Zimand.

Connected through hyperedge HE-1 (induced by source paper "universal almost optimal compression and slepian wolf coding in probabilistic polynomial time"):
  with members:
    - "coding in the fork network in the framework of kolmogorov complexity"
    - "kolmogorov complexity version of slepian wolf coding"
    - "short lists with short programs in short time"
    - "short lists with short programs in short time a short proof"
    - "linear list approximation for short programs or the power of a few random bits"
    - "variations on muchnik s conditional complexity theorem"

Connected through hyperedge HE-2 (induced by source paper "optimal probabilistic polynomial time compression and the slepian wolf theorem tighter version and simple proofs"):
  with members:
    - "kolmogorov complexity version of slepian wolf coding"
    - "linear list approximation for short programs or the power of a few random bits"

Connected through hyperedge HE-3 (induced by source paper "compression of data streams down to their information content"):
  with members:
    - "forbidden information"
    - "lower bounds on the redundancy in computations from random oracles via betting strategies with restricted wagers"
    - "short lists with short programs in short time"
    - "linear list approximation for short programs or the power of a few random bits"
    - "some theorems on the algorithmic approach to probability theory and information theory"
    - "dimension extractors and optimal decompression"
    - "every sequence is decompressible from a random one"

Connected through hyperedge HE-4 (induced by source paper "list approximation for increasing kolmogorov complexity"):
  with members:
    - "kolmogorov complexity version of slepian wolf coding"
    - "short lists with short programs in short time"
    - "short lists with short programs in short time a short proof"
    - "linear list approximation for short programs or the power of a few random bits"

Connected through hyperedge HE-5 (induced by source paper "kolmogorov complexity version of slepian wolf coding"):
  with members:
    - "coding in the fork network in the framework of kolmogorov complexity"
    - "short lists with short programs in short time"
    - "short lists with short programs in short time a short proof"
    - "linear list approximation for short programs or the power of a few random bits"
    - "complexity of complexity and strings with maximal plain and prefix kolmogorov complexity"
    - "variations on muchnik s conditional complexity theorem"

Connected through hyperedge HE-6 (induced by source paper "short lists with short programs in short time"):
  with members:
    - "short lists with short programs in short time a short proof"
    - "space bounded kolmogorov extractors"
    - "nonuniform kolmogorov extractors"
    - "complexity of complexity and strings with maximal plain and prefix kolmogorov complexity"
    - "possibilities and impossibilities in kolmogorov complexity extraction"
    - "symmetry of information and bounds on nonuniform randomness extraction via kolmogorov extractors"
    - "improving the space bounded version of muchnik s conditional complexity theorem via naive derandomization"
    - "variations on muchnik s conditional complexity theorem"

Connected through hyperedge HE-7 (induced by source paper "short lists with short programs in short time a short proof"):
  with members:
    - "short lists with short programs in short time"
    - "linear list approximation for short programs or the power of a few random bits"
    - "variations on muchnik s conditional complexity theorem"

Connected through hyperedge HE-8 (induced by source paper "linear list approximation for short programs or the power of a few random bits"):
  with members:
    - "short lists with short programs in short time"
    - "short lists with short programs in short time a short proof"

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)