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 "deterministic graph cuts in subquadratic time sparse balanced and k vertex"):
  Abstract: We study deterministic algorithms for computing graph cuts, with focus on two fundamental problems: balanced sparse cut and $k$-vertex connectivity for small $k$ ($k=O(\polylog n)$). Both problems can be solved in near-linear time with randomized algorithms, but their previous deterministic counterparts take at least quadratic time. In this paper, we break this bound for both problems. Interestingly, achieving this for one problem crucially relies on doing so for the other. #R##N#In particular, via a divide-and-conquer argument, a variant of the cut-matching game by [Khandekar et al.`07], and the local vertex connectivity algorithm of [Nanongkai et al. STOC'19], we give a subquadratic time algorithm for $k$-vertex connectivity using a subquadratic time algorithm for computing balanced sparse cuts on sparse graphs. To achieve the latter, we improve the previously best $mn$ bound for approximating balanced sparse cut for the whole range of $m$. This starts from (1) breaking the $n^3$ barrier on dense graphs to $n^{\omega + o(1)}$ (where $\omega < 2.372$) using the the PageRank matrix, but without explicitly sweeping to find sparse cuts; to (2) getting the $\tilde O(m^{1.58})$ bound by combining the $J$-trees by [Madry FOCS `10] with the $n^{\omega + o(1)}$ bound above, and finally; to (3) getting the $m^{1.5 + o(1)}$ bound by recursively invoking the second bound in conjunction with expander-based graph sparsification. Interestingly, our final $m^{1.5 + o(1)}$ bound lands at a natural stopping point in the sense that polynomially breaking it would lead to a breakthrough for the dynamic connectivity problem.

Includes members:
  Member "a faster local algorithm for detecting bounded size cuts with applications to higher connectivity problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "vertex sparsifiers for c edge connectivity")
  Member "computing and testing small vertex connectivity in near linear time and queries":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "computing and testing small connectivity in near linear time and queries via fast local cut algorithms")
  Member "a deterministic algorithm for balanced cut with applications to dynamic connectivity flows and beyond":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "faster divergence maximization for faster maximum flow")
  Member "distributed edge connectivity in sublinear time":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a deterministic algorithm for balanced cut with applications to dynamic connectivity flows and beyond")
  Member "breaking quadratic time for small vertex connectivity and an approximation scheme":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a deterministic algorithm for balanced cut with applications to dynamic connectivity flows and beyond")
  Member "graph sketching against adaptive adversaries applied to the minimum degree algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "non monotone submodular maximization with nearly optimal adaptivity and query complexity")
  Member "expander decomposition and pruning faster stronger and simpler":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "faster algorithms for computing maximal 2 connected subgraphs in sparse directed graphs":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "computing and testing small connectivity in near linear time and queries via fast local cut algorithms")

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)