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: "breaking quadratic time for small vertex connectivity and an approximation scheme"
  Abstract: Vertex connectivity a classic extensively-studied problem. Given an integer $k$, its goal is to decide if an $n$-node $m$-edge graph can be disconnected by removing $k$ vertices. Although a linear-time algorithm was postulated since 1974 [Aho, Hopcroft and Ullman], and despite its sibling problem of edge connectivity being resolved over two decades ago [Karger STOC'96], so far no vertex connectivity algorithms are faster than $O(n^2)$ time even for $k=4$ and $m=O(n)$. In the simplest case where $m=O(n)$ and $k=O(1)$, the $O(n^2)$ bound dates five decades back to [Kleitman IEEE Trans. Circuit Theory'69]. For general $k$ and $m$, the best bound is $\tilde{O}(\min(kn^2, n^\omega+nk^\omega))$. #R##N#In this paper, we present a randomized Monte Carlo algorithm with $\tilde{O}(m+k^{7/3}n^{4/3})$ time for any $k=O(\sqrt{n})$. This gives the {\em first subquadratic time} bound for any $4\leq k \leq o(n^{2/7})$ and improves all above classic bounds for all $k\le n^{0.44}$. We also present a new randomized Monte Carlo $(1+\epsilon)$-approximation algorithm that is strictly faster than the previous Henzinger's 2-approximation algorithm [J. Algorithms'97] and all previous exact algorithms. #R##N#The key to our results is to avoid computing single-source connectivity, which was needed by all previous exact algorithms and is not known to admit $o(n^2)$ time. Instead, we design the first local algorithm for computing vertex connectivity; without reading the whole graph, our algorithm can find a separator of size at most $k$ or certify that there is no separator of size at most $k$ `near' a given seed node.

Connected through hyperedge HE-1 (induced by source paper "a deterministic algorithm for balanced cut with applications to dynamic connectivity flows and beyond"):
  with members:
    - "faster p norm minimizing flows via smoothed q norm problems"
    - "fast provably convergent irls algorithm for p norm linear regression"
    - "distributed edge connectivity in sublinear time"
    - "improved distributed expander decomposition and nearly optimal triangle enumeration"
    - "flows in almost linear time via adaptive preconditioning"
    - "a new algorithm for decremental single source shortest paths with applications to vertex capacitated flow and cut problems"
    - "graph sparsification spectral sketches and faster resistance computation via short cycle decompositions"
    - "short cycles via low diameter decompositions"

Connected through hyperedge HE-2 (induced by source paper "deterministic graph cuts in subquadratic time sparse balanced and k vertex"):
  with members:
    - "a faster local algorithm for detecting bounded size cuts with applications to higher connectivity problems"
    - "computing and testing small vertex connectivity in near linear time and queries"
    - "a deterministic algorithm for balanced cut with applications to dynamic connectivity flows and beyond"
    - "distributed edge connectivity in sublinear time"
    - "graph sketching against adaptive adversaries applied to the minimum degree algorithm"
    - "expander decomposition and pruning faster stronger and simpler"
    - "faster algorithms for computing maximal 2 connected subgraphs in sparse directed graphs"
    - "local flow partitioning for faster edge connectivity"

Connected through hyperedge HE-3 (induced by source paper "a new deterministic algorithm for dynamic set cover"):
  with members:
    - "dynamic matrix inverse improved algorithms and matching conditional lower bounds"
    - "a new algorithm for decremental single source shortest paths with applications to vertex capacitated flow and cut problems"
    - "a deamortization approach for dynamic spanner and dynamic maximal matching"
    - "fully dynamic approximate maximum matching and minimum vertex cover in o log 3 n worst case update time"
    - "dynamic minimum spanning forest with subpolynomial worst case update time"
    - "deterministic fully dynamic approximate vertex cover and fractional matching in o 1 amortized update time"
    - "fully dynamic maximal matching in constant update time"
    - "new deterministic approximation algorithms for fully dynamic matching"

Connected through hyperedge HE-4 (induced by source paper "vertex sparsifiers for c edge connectivity"):
  with members:
    - "a faster local algorithm for detecting bounded size cuts with applications to higher connectivity problems"
    - "fully dynamic spectral vertex sparsifiers and applications"
    - "dynamic effective resistances and approximate schur complement on separable graphs"
    - "expander decomposition and pruning faster stronger and simpler"
    - "improved guarantees for vertex sparsification in planar graphs"
    - "the power of vertex sparsifiers in dynamic graph algorithms"
    - "sampling random spanning trees faster than matrix multiplication"
    - "on fully dynamic graph sparsifiers"

Connected through hyperedge HE-5 (induced by source paper "computing and testing small connectivity in near linear time and queries via fast local cut algorithms"):
  with members:
    - "a faster local algorithm for detecting bounded size cuts with applications to higher connectivity problems"
    - "computing and testing small vertex connectivity in near linear time and queries"
    - "a new algorithm for decremental single source shortest paths with applications to vertex capacitated flow and cut problems"
    - "expander decomposition and pruning faster stronger and simpler"
    - "faster algorithms for computing maximal 2 connected subgraphs in sparse directed graphs"
    - "on sampling edges almost uniformly"
    - "local flow partitioning for faster edge connectivity"
    - "on fully dynamic graph sparsifiers"

Connected through hyperedge HE-6 (induced by source paper "a faster local algorithm for detecting bounded size cuts with applications to higher connectivity problems"):
  with members:
    - "faster algorithms for computing maximal 2 connected subgraphs in sparse directed graphs"
    - "local flow partitioning for faster edge connectivity"
    - "on fully dynamic graph sparsifiers"
    - "powers of tensors and fast matrix multiplication"
    - "deterministic edge connectivity in near linear time"
    - "distributed computation of large scale graph problems"
    - "fast local computation algorithms"
    - "minimum cuts in near linear time"

Connected through hyperedge HE-7 (induced by source paper "computing and testing small vertex connectivity in near linear time and queries"):
  with members:
    - "a faster local algorithm for detecting bounded size cuts with applications to higher connectivity problems"
    - "a new algorithm for decremental single source shortest paths with applications to vertex capacitated flow and cut problems"
    - "faster algorithms for computing maximal 2 connected subgraphs in sparse directed graphs"
    - "distributed connectivity decomposition"

Connected through hyperedge HE-8 (induced by source paper "funseqset towards a purely functional data structure for the linearisation case of dynamic trees problem"):
  with members:
    - "a rearrangement distance for fully labelled trees"

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)