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 "massively parallel similarity join edge isoperimetry and distance correlations on the hypercube"):
  Abstract: We study distributed protocols for finding all pairs of similar vectors in a large dataset. Our results pertain to a variety of discrete metrics, and we give concrete instantiations for Hamming distance. In particular, we give improved upper bounds on the overhead required for similarity defined by Hamming distance $r>1$ and prove a lower bound showing qualitative optimality of the overhead required for similarity over any Hamming distance $r$. Our main conceptual contribution is a connection between similarity search algorithms and certain graph-theoretic quantities. For our upper bounds, we exhibit a general method for designing one-round protocols using edge-isoperimetric shapes in similarity graphs. For our lower bounds, we define a new combinatorial optimization problem, which can be stated in purely graph-theoretic terms yet also captures the core of the analysis in previous theoretical work on distributed similarity joins. As one of our main technical results, we prove new bounds on distance correlations in subsets of the Hamming cube.

Includes members:
  Member "scalability and total recall with fast coveringlsh":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimal las vegas approximate near neighbors in ell_p")
  Member "learning to hash for indexing big data a survey":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "random vlad based deep hashing for efficient image retrieval")
  Member "high speed hashing for integers and strings":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "peeling close to the orientability threshold spatial coupling in hashing based data structures")
  Member "locality sensitive hashing without false negatives":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "similarity problems in high dimensions")
  Member "probabilistic polynomials and hamming nearest neighbors":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "algorithms for similarity search and pseudorandomness")
  Member "lower bounds on near neighbor search via metric expansion":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "tight static lower bounds for non adaptive data structures")
  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")

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)