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 "sensitive distance and reachability oracles for large batch updates"):
  Abstract: In the sensitive distance oracle problem, there are three phases. We first preprocess a given directed graph $G$ with $n$ nodes and integer weights from $[-W,W]$. Second, given a single batch of $f$ edge insertions and deletions, we update the data structure. Third, given a query pair of nodes $(u,v)$, return the distance from $u$ to $v$. In the easier problem called sensitive reachability oracle problem, we only ask if there exists a directed path from $u$ to $v$. #R##N#Our first result is a sensitive distance oracle with $\tilde{O}(Wn^{\omega+(3-\omega)\mu})$ preprocessing time, $\tilde{O}(Wn^{2-\mu}f^{2}+Wnf^{\omega})$ update time, and $\tilde{O}(Wn^{2-\mu}f+Wnf^{2})$ query time where the parameter $\mu\in[0,1]$ can be chosen. The data-structure requires $O(Wn^{2+\mu} \log n)$ bits of memory. This is the first algorithm that can handle $f\ge\log n$ updates. Previous results (e.g. [Demetrescu et al. SICOMP'08; Bernstein and Karger SODA'08 and FOCS'09; Duan and Pettie SODA'09; Grandoni and Williams FOCS'12]) can handle at most 2 updates. When $3\le f\le\log n$, the only non-trivial algorithm was by [Weimann and Yuster FOCS'10]. When $W=\tilde{O}(1)$, our algorithm simultaneously improves their preprocessing time, update time, and query time. In particular, when $f=\omega(1)$, their update and query time is $\Omega(n^{2-o(1)})$, while our update and query time are truly subquadratic in $n$, i.e., ours is faster by a polynomial factor of $n$. To highlight the technique, ours is the first graph algorithm that exploits the kernel basis decomposition of polynomial matrices by [Jeannerod and Villard J.Comp'05; Zhou, Labahn and Storjohann J.Comp'15] developed in the symbolic computation community. #R##N#[...]

Includes members:
  Member "dynamic matrix inverse improved algorithms and matching conditional lower bounds":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "solving tall dense linear programs in nearly linear time")
  Member "deterministic combinatorial replacement paths and distance sensitivity oracles":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "small cuts and connectivity certificates a fault tolerant approach")
  Member "dynamic approximate shortest paths and beyond subquadratic and worst case update time":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deterministic algorithms for decremental approximate shortest paths faster and simpler")
  Member "conditional hardness for sensitivity problems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "fine grained complexity meets ip pspace")
  Member "fast deterministic computation of the hermite normal form and determinant of a polynomial matrix":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "implementations of efficient univariate polynomial matrix algorithms and application to bivariate resultants")
  Member "connectivity oracles for graphs subject to vertex failures":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "approximate distance oracles subject to multiple vertex failures")
  Member "incremental and fully dynamic subgraph connectivity for emergency planning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "connectivity oracles for graphs subject to vertex failures")
  Member "powers of tensors and fast matrix multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")

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)