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: "additive spanners and distance oracles in quadratic time"
  Abstract: Let $G$ be an unweighted, undirected graph. An additive $k$-spanner of $G$ is a subgraph $H$ that approximates all distances between pairs of nodes up to an additive error of $+k$, that is, it satisfies $d_H(u,v) \le d_G(u,v)+k$ for all nodes $u,v$, where $d$ is the shortest path distance. We give a deterministic algorithm that constructs an additive $O\!\left(1\right)$-spanner with $O\!\left(n^{4/3}\right)$ edges in $O\!\left(n^2\right)$ time. This should be compared with the randomized Monte Carlo algorithm by Woodruff [ICALP 2010] giving an additive $6$-spanner with $O\!\left(n^{4/3}\log^3 n\right)$ edges in expected time $O\!\left(n^2\log^2 n\right)$. #R##N#An $(\alpha,\beta)$-approximate distance oracle for $G$ is a data structure that supports the following distance queries between pairs of nodes in $G$. Given two nodes $u$, $v$ it can in constant time compute a distance estimate $\tilde{d}$ that satisfies $d \le \tilde{d} \le \alpha d + \beta$ where $d$ is the distance between $u$ and $v$ in $G$. Sommer [ICALP 2016] gave a randomized Monte Carlo $(2,1)$-distance oracle of size $O\!\left(n^{5/3}\text{poly} \log n\right)$ in expected time $O\!\left(n^2\text{poly} \log n\right)$. As an application of the additive $O(1)$-spanner we improve the construction by Sommer [ICALP 2016] and give a Las Vegas $(2,1)$-distance oracle of size $O\!\left(n^{5/3}\right)$ in time $O\!\left(n^2\right)$. This also implies an algorithm that in $O\!\left(n^2\right)$ gives approximate distance for all pairs of nodes in $G$ improving on the $O\!\left(n^2 \log n\right)$ algorithm by Baswana and Kavitha [SICOMP 2010].

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 "towards tight approximation bounds for graph diameter and eccentricities"):
  with members:
    - "tight hardness for shortest cycles and paths in sparse graphs"
    - "improved rectangular matrix multiplication using powers of the coppersmith winograd tensor"
    - "the 4 3 additive spanner exponent is tight"
    - "powers of tensors and fast matrix multiplication"
    - "faster all pairs shortest paths via circuit complexity"
    - "faster algorithms for rectangular matrix multiplication"
    - "algorithmic applications of baur strassen s theorem shortest cycles diameter and matchings"
    - "all pairs shortest paths using bridging sets and rectangular matrix multiplication"

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)