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 "non monotone submodular maximization in exponentially fewer iterations"):
  Abstract: In this paper we consider parallelization for applications whose objective can be expressed as maximizing a non-monotone submodular function under a cardinality constraint. Our main result is an algorithm whose approximation is arbitrarily close to $1/2e$ in $O(\log^2 n)$ adaptive rounds, where $n$ is the size of the ground set. This is an exponential speedup in parallel running time over any previously studied algorithm for constrained non-monotone submodular maximization. Beyond its provable guarantees, the algorithm performs well in practice. Specifically, experiments on traffic monitoring and personalized data summarization applications show that the algorithm finds solutions whose values are competitive with state-of-the-art algorithms while running in exponentially fewer parallel iterations.

Includes members:
  Member "an exponential speedup in parallel running time for submodular maximization without loss in approximation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "approximability of monotone submodular function maximization under cardinality and matroid constraints in the streaming model")
  Member "submodular maximization with nearly optimal approximation and adaptivity in nearly linear time":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "approximability of monotone submodular function maximization under cardinality and matroid constraints in the streaming model")
  Member "an adaptivity hierarchy theorem for property testing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "noisy source location on a line")
  Member "settling the query complexity of non adaptive junta testing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "almost optimal testers for concise representations")
  Member "parallel algorithms for select and partition with noisy comparisons":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "locally private hypothesis selection")
  Member "constrained submodular maximization beyond 1 e":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "optimal streaming algorithms for submodular maximization with cardinality constraints")
  Member "the non adaptive query complexity of testing k parities":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an exponential speedup in parallel running time for submodular maximization without loss in approximation")
  Member "on the power of adaptivity in sparse recovery":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "stronger l2 l2 compressed sensing without iterating")

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.DS(Data Structures and Algorithms)