human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "approximating spanners and directed steiner forest upper and lower bounds"
  Abstract: It was recently found that there are very close connections between the existence of additive spanners (subgraphs where all distances are preserved up to an additive stretch), distance preservers (subgraphs in which demand pairs have their distance preserved exactly), and pairwise spanners (subgraphs in which demand pairs have their distance preserved up to a multiplicative or additive stretch) [Abboud-Godwin SODA '16, Godwin-Williams SODA '16]. We study these problems from an optimization point of view, where rather than studying the existence of extremal instances we are given an instance and are asked to find the sparsest possible spanner/preserver. We give an $O(n^{3/5 + \epsilon})$-approximation for distance preservers and pairwise spanners (for arbitrary constant $\epsilon > 0$). This is the first nontrivial upper bound for either problem, both of which are known to be as hard to approximate as Label Cover. We also prove Label Cover hardness for approximating additive spanners, even for the cases of additive 1 stretch (where one might expect a polylogarithmic approximation, since the related multiplicative 2-spanner problem admits an $O(\log n)$-approximation) and additive polylogarithmic stretch (where the related multiplicative spanner problem has an $O(1)$-approximation). #R##N#Interestingly, the techniques we use in our approximation algorithm extend beyond distance-based problem to pure connectivity network design problems. In particular, our techniques allow us to give an $O(n^{3/5 + \epsilon})$-approximation for the Directed Steiner Forest problem (for arbitrary constant $\epsilon > 0$) when all edges have uniform costs, improving the previous best $O(n^{2/3 + \epsilon})$-approximation due to Berman et al.~[ICALP '11] (which holds for general edge costs).

Connected through hyperedge HE-1 (induced by source paper "graph spanners a tutorial review"):
  with members:
    - "near additive spanners and near exact hopsets a unified view"
    - "some general structure for extremal sparsification problems"
    - "weighted additive spanners"
    - "near additive spanners in low polynomial deterministic congest time"
    - "multi level graph sketches via single level solvers"
    - "almost shortest paths and pram distance oracles in weighted graphs"
    - "an fpt algorithm for minimum additive spanner problem"
    - "distributed construction of light networks"

Connected through hyperedge HE-2 (induced by source paper "lasserre integrality gaps for graph spanners and related problems"):
  with members:
    - "characterizing demand graphs for fixed parameter shallow light steiner network"
    - "parallel metric tree embedding based on an algebraic view on moore bellman ford"
    - "everywhere sparse spanners via dense subgraphs"
    - "label cover instances with large girth and the hardness of approximating basic k spanner"
    - "rounding semidefinite programming hierarchies via global correlation"
    - "fault tolerant spanners better and simpler"
    - "directed steiner tree and the lasserre hierarchy"
    - "directed spanners via flow based linear programs"

Connected through hyperedge HE-3 (induced by source paper "distributed spanner approximation"):
  with members:
    - "distributed approximation of minimum k edge connected spanning subgraphs"
    - "improved deterministic distributed construction of spanners"
    - "distributed property testing for subgraph freeness revisited"
    - "quadratic and near quadratic lower bounds for the congest model"
    - "on derandomizing local distributed algorithms"
    - "distributed distance bounded network design through distributed convex programming"
    - "near linear lower bounds for distributed distance computations even in sparse networks"
    - "efficient algorithms for constructing very sparse spanners and emulators"

Connected through hyperedge HE-4 (induced by source paper "eth hardness of approximating 2 csps and directed steiner network"):
  with members:
    - "hardness of approximate nearest neighbor search"
    - "on the hardness of approximate and exact bichromatic maximum inner product"
    - "improved approximation algorithms for projection games"
    - "distributed pcp theorems for hardness of approximation in p"
    - "detecting communities is hard and counting them is even harder"
    - "settling the complexity of computing approximate two player nash equilibria"
    - "approximation of non boolean 2csp"
    - "polynomially low error pcps with polyloglog n queries via modular composition"

Connected through hyperedge HE-5 (induced by source paper "distance preserving graph contractions"):
  with members:
    - "graph sparsification spectral sketches and faster resistance computation via short cycle decompositions"
    - "sampling random spanning trees faster than matrix multiplication"
    - "linear size distance preservers"
    - "graph minors for preserving terminal distances approximately lower and upper bounds"
    - "approximate gaussian elimination for laplacians fast sparse and simple"
    - "better distance preservers and additive spanners"
    - "the 4 3 additive spanner exponent is tight"
    - "towards resistance sparsifiers"

Question: Please tell me which class the center node 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)