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 "new techniques and tighter bounds for local computation algorithms"):
  Abstract: Given an input $x$, and a search problem $F$, local computation algorithms (LCAs) implement access to specified locations of $y$ in a legal output $y \in F(x)$, using polylogarithmic time and space. Mansour et al., (2012), had previously shown how to convert certain online algorithms to LCAs. In this work, we expand on that line of work and develop new techniques for designing LCAs and bounding their space and time complexity. Our contributions are fourfold: (1) We significantly improve the running times and space requirements of LCAs for previous results, (2) we expand and better define the family of online algorithms which can be converted to LCAs using our techniques, (3) we show that our results apply to a larger family of graphs than that of previous results, and (4) our proofs are simpler and more concise than the previous proof methods. #R##N#For example, we show how to construct LCAs that require $O(\log{n}\log\log{n})$ space and $O(\log^2{n})$ time (and expected time $O(\log\log{n})$) for problems such as maximal matching on a large family of graphs, as opposed to the henceforth best results that required $O(\log^3{n})$ space and $O(\log^4{n})$ time, and applied to a smaller family of graphs.

Includes members:
  Member "local computation algorithms for graphs of non constant degrees":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "seeing far vs seeing wide volume complexity of local graph problems")
  Member "an improved distributed algorithm for maximal independent set":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "space efficient approximation to maximum matching size from uniform edge samples")
  Member "distributed maximum matching in bounded degree graphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "distributed maximum matching verification in congest")
  Member "a local computation approximation scheme to maximum matching":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "distributed maximum matching verification in congest")
  Member "local computation mechanism design":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "local computation algorithms for the lovasz local lemma")
  Member "the locality of distributed symmetry breaking":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "distributed maximum matching verification in congest")
  Member "converting online algorithms to local computation algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "seeing far vs seeing wide volume complexity of local graph problems")
  Member "space efficient local computation algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "seeing far vs seeing wide volume complexity of local graph problems")

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)