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 "fast cross polytope locality sensitive hashing"):
  Abstract: We provide a variant of cross-polytope locality sensitive hashing with respect to angular distance which is provably optimal in asymptotic sensitivity and enjoys $\mathcal{O}(d \ln d )$ hash computation time. Building on a recent result (by Andoni, Indyk, Laarhoven, Razenshteyn, Schmidt, 2015), we show that optimal asymptotic sensitivity for cross-polytope LSH is retained even when the dense Gaussian matrix is replaced by a fast Johnson-Lindenstrauss transform followed by discrete pseudo-rotation, reducing the hash computation time from $\mathcal{O}(d^2)$ to $\mathcal{O}(d \ln d )$. Moreover, our scheme achieves the optimal rate of convergence for sensitivity. By incorporating a low-randomness Johnson-Lindenstrauss transform, our scheme can be modified to require only $\mathcal{O}(\ln^9(d))$ random bits

Includes members:
  Member "the restricted isometry property of subsampled fourier matrices":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "one shot neural architecture search via compressive sensing")
  Member "practical and optimal lsh for angular distance":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "differentiable reasoning over a virtual knowledge base")
  Member "optimal data dependent hashing for approximate near neighbors":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "autoblock a hands off blocking framework for entity matching")
  Member "the johnson lindenstrauss lemma is optimal for linear dimensionality reduction":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "sub gaussian matrices on sets optimal tail dependence and applications")
  Member "sparser johnson lindenstrauss transforms":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sketching transformed matrices with applications to natural language processing")
  Member "new and improved johnson lindenstrauss embeddings via the restricted isometry property":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "finding the mode of a kernel density estimate")
  Member "optimal lower bounds for locality sensitive hashing except when q is tiny":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a survey on deep hashing methods")
  Member "lower bounds on locality sensitive hashing":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "algorithms for similarity search and pseudorandomness")

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)