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 "better distance preservers and additive spanners"):
  Abstract: We make improvements to the upper bounds on several popular types of distance preserving graph sketches. These sketches are all various restrictions of the {\em additive pairwise spanner} problem, in which one is given an undirected unweighted graph $G$, a set of node pairs $P$, and an error allowance $+\beta$, and one must construct a sparse subgraph $H$ satisfying $\delta_H(u, v) \le \delta_G(u, v) + \beta$ for all $(u, v) \in P$. #R##N#The first part of our paper concerns {\em pairwise distance preservers}, which make the restriction $\beta=0$ (i.e. distances must be preserved {\em exactly}). Our main result here is an upper bound of $|H| = O(n^{2/3}|P|^{2/3} + n|P|^{1/3})$ when $G$ is undirected and unweighted. This improves on existing bounds whenever $|P| = \omega(n^{3/4})$, and it is the first such improvement in the last ten years. #R##N#We then devise a new application of distance preservers to graph clustering algorithms, and we apply this algorithm to {\em subset spanners}, which require $P = S \times S$ for some node subset $S$, and {\em (standard) spanners}, which require $P = V \times V$. For both of these objects, our construction generalizes the best known bounds when the error allowance is constant, and we obtain the strongest polynomial error/sparsity tradeoff that has yet been reported (in fact, for subset spanners, ours is the {\em first} nontrivial construction that enjoys improved sparsity from a polynomial error allowance). #R##N#We leave open a conjecture that $O(n^{2/3}|P|^{2/3} + n)$ pairwise distance preservers are possible for undirected unweighted graphs. Resolving this conjecture in the affirmative would improve and simplify our upper bounds for all the graph sketches mentioned above.

Includes members:
  Member "the greedy spanner is existentially optimal":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a polynomial time algorithm for almost optimal vertex fault tolerant spanners")
  Member "a hierarchy of lower bounds for sublinear additive spanners":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "exponentially faster shortest paths in the congested clique")
  Member "linear size distance preservers":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "weighted additive spanners")
  Member "a linear size logarithmic stretch path reporting distance oracle for general graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on strong diameter padded decompositions")
  Member "very sparse additive spanners and emulators":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "lower bounds on sparse spanners emulators and diameter reducing shortcuts")
  Member "additive spanners a simple construction":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "weighted additive spanners")
  Member "on pairwise spanners":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "weighted additive spanners")
  Member "nearly linear time algorithms for graph partitioning graph sparsification and solving linear systems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "compressive sensing for cut improvement and local clustering")

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)