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: "edge estimation with independent set oracles"
  Abstract: We study the problem of estimating the number of edges in a graph with access to only an independent set oracle. Independent set queries draw motivation from group testing and have applications to the complexity of decision versus counting problems. We give two algorithms to estimate the number of edges in an $n$-vertex graph: one that uses only $\mathrm{polylog}(n)$ bipartite independent set queries, and another one that uses ${n}^{2/3}\cdot \mathrm{polylog}(n)$ independent set queries.

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"
    - "the hardness of embedding grids and walls"
    - "randomised enumeration of small witnesses using a decision oracle"
    - "the challenges of unbounded treewidth in parameterised subgraph counting problems"

Connected through hyperedge HE-2 (induced by source paper "near neighbor who is the fairest of them all"):
  with members:
    - "fair algorithms for clustering"
    - "scalable fair clustering"
    - "independent range sampling revisited again"
    - "fair near neighbor search independent range sampling in high dimensions"
    - "convex formulations for fair principal component analysis"
    - "fair clustering through fairlets"
    - "fair algorithms for learning in allocation problems"
    - "a reductions approach to fair classification"

Connected through hyperedge HE-3 (induced by source paper "nearly optimal edge estimation with independent set queries"):
  with members:
    - "a simple sublinear time algorithm for counting arbitrary subgraphs via edge sampling"
    - "fiding forbidden minors in sublinear time a o n 1 2 o 1 query one sided tester for minor closed properties on bounded degree graphs"
    - "on approximating the number of k cliques in sublinear time"
    - "on sampling edges almost uniformly"
    - "sublinear time algorithms for counting star subgraphs with applications to join selectivity estimation"
    - "approximately counting triangles in sublinear time"
    - "the power of an example hidden set size approximation using group queries and conditional sampling"
    - "a near optimal sublinear time algorithm for approximating the minimum vertex cover size"

Connected through hyperedge HE-4 (induced by source paper "inner product oracle can estimate and sample"):
  with members:
    - "sublinear time numerical linear algebra for structured matrices"
    - "fine grained reductions from approximate counting to decision"
    - "testing matrix rank optimally"
    - "on sampling edges almost uniformly"
    - "computing exact minimum cuts without knowing the graph"
    - "approximately counting triangles in sublinear time"
    - "the power of an example hidden set size approximation using group queries and conditional sampling"

Connected through hyperedge HE-5 (induced by source paper "hyperedge estimation using polylogarithmic subset queries"):
  with members:
    - "parameterized query complexity of hitting set using stability of sunflowers"
    - "fine grained reductions from approximate counting to decision"
    - "on approximating the number of k cliques in sublinear time"
    - "computing exact minimum cuts without knowing the graph"
    - "approximately counting triangles in sublinear time"
    - "the power of an example hidden set size approximation using group queries and conditional sampling"
    - "finding cycles and trees in sublinear time"

Connected through hyperedge HE-6 (induced by source paper "a lower bound on cycle finding in sparse digraphs"):
  with members:
    - "a simple sublinear time algorithm for counting arbitrary subgraphs via edge sampling"
    - "fiding forbidden minors in sublinear time a o n 1 2 o 1 query one sided tester for minor closed properties on bounded degree graphs"
    - "on approximating the number of k cliques in sublinear time"
    - "approximately counting triangles in sublinear time"
    - "property testing in sparse directed graphs 3 star freeness and connectivity"
    - "a near optimal sublinear time algorithm for approximating the minimum vertex cover size"

Connected through hyperedge HE-7 (induced by source paper "fine grained reductions from approximate counting to decision"):
  with members:
    - "clustered integer 3sum via additive combinatorics"
    - "faster all pairs shortest paths via circuit complexity"
    - "exploiting independent subformulas a faster approximation scheme for k sat"
    - "the relative exponential time complexity of approximate counting satisfying assignments"
    - "a satisfiability algorithm for ac 0"
    - "3 sat faster and simpler unique sat bounds for ppsz hold in general"
    - "an approximation algorithm for k sat"

Connected through hyperedge HE-8 (induced by source paper "parameterized query complexity of hitting set using stability of sunflowers"):
  with members:
    - "set cover in sub linear time"
    - "computing exact minimum cuts without knowing the graph"
    - "a near optimal sublinear time algorithm for approximating the minimum vertex cover size"

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)