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: "randomised enumeration of small witnesses using a decision oracle"
  Abstract: Many combinatorial problems involve determining whether a universe of $n$ elements contains a witness consisting of $k$ elements which have some specified property. In this paper we investigate the relationship between the decision and enumeration versions of such problems: efficient methods are known for transforming a decision algorithm into a search procedure that finds a single witness, but even finding a second witness is not so straightforward in general. We show that, if the decision version of the problem can be solved in time $f(k) \cdot poly(n)$, there is a randomised algorithm which enumerates all witnesses in time $e^{k + o(k)} \cdot f(k) \cdot poly(n) \cdot N$, where $N$ is the total number of witnesses. If the decision version of the problem is solved by a randomised algorithm which may return false negatives, then the same method allows us to output a list of witnesses in which any given witness will be included with high probability. The enumeration algorithm also gives rise to an efficient algorithm to count the total number of witnesses when this number is small.

Connected through hyperedge HE-1 (induced by source paper "approximately counting and sampling small witnesses using a colourful decision oracle"):
  with members:
    - "counting answers to existential questions"
    - "zeros of holant problems locations and algorithms"
    - "more consequences of falsifying seth and the orthogonal vectors conjecture"
    - "fine grained reductions from approximate counting to decision"
    - "near optimal linear decision trees for k sum and related problems"
    - "edge estimation with independent set oracles"
    - "the hardness of embedding grids and walls"
    - "the challenges of unbounded treewidth in parameterised subgraph counting problems"

Connected through hyperedge HE-2 (induced by source paper "which np hard sat and csp problems admit exponentially improved algorithms"):
  with members:
    - "kernelization of constraint satisfaction problems a study through universal algebra"
    - "the proof of csp dichotomy conjecture"
    - "tight hardness for shortest cycles and paths in sparse graphs"
    - "time complexity of constraint satisfaction via universal algebra"
    - "on problems as hard as cnf sat"
    - "exact algorithms via monotone local search"
    - "powers of tensors and fast matrix multiplication"
    - "analysis of boolean functions"

Connected through hyperedge HE-3 (induced by source paper "efficiently enumerating hitting sets of hypergraphs arising in data profiling"):
  with members:
    - "the minimal hitting set generation problem algorithms and computation"
    - "exploiting hidden structure in selecting dimensions that distinguish vectors"
    - "efficient enumeration of solutions produced by closure operations"
    - "a polynomial delay algorithm for enumerating minimal dominating sets in chordal graphs"
    - "paradigms for parameterized enumeration"
    - "efficient algorithms for dualizing large scale hypergraphs"
    - "new results on monotone dualization and generating hypergraph transversals"
    - "incremental recompilation of knowledge"

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)