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: "pseudo random graphs and bit probe schemes with one sided error"
  Abstract: We study probabilistic bit-probe schemes for the membership problem. Given a set A of at most n elements from the universe of size m we organize such a structure that queries of type "Is x in A?" can be answered very quickly. H.Buhrman, P.B.Miltersen, J.Radhakrishnan, and S.Venkatesh proposed a bit-probe scheme based on expanders. Their scheme needs space of $O(n\log m)$ bits, and requires to read only one randomly chosen bit from the memory to answer a query. The answer is correct with high probability with two-sided errors. In this paper we show that for the same problem there exists a bit-probe scheme with one-sided error that needs space of $O(n\log^2 m+\poly(\log m))$ bits. The difference with the model of Buhrman, Miltersen, Radhakrishnan, and Venkatesh is that we consider a bit-probe scheme with an auxiliary word. This means that in our scheme the memory is split into two parts of different size: the main storage of $O(n\log^2 m)$ bits and a short word of $\log^{O(1)}m$ bits that is pre-computed once for the stored set A and `cached'. To answer a query "Is x in A?" we allow to read the whole cached word and only one bit from the main storage. For some reasonable values of parameters our space bound is better than what can be achieved by any scheme without cached data.

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"
    - "impossibility of independence amplification in kolmogorov complexity theory"
    - "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 "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"
    - "impossibility of independence amplification in kolmogorov complexity theory"
    - "extracting the kolmogorov complexity of strings and sequences from sources with limited independence"
    - "variations on muchnik s conditional complexity theorem"

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.DS(Data Structures and Algorithms)