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: "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#[...]

Connected through hyperedge HE-1 (induced by source paper "approximate distance oracles subject to multiple vertex failures"):
  with members:
    - "generic single edge fault tolerant exact distance oracle"
    - "a trivial yet optimal solution to vertex fault tolerant spanners"
    - "exact distance oracles for planar graphs with failing vertices"
    - "preserving distances in very faulty graphs"
    - "optimal vertex fault tolerant spanners for fixed stretch"
    - "connectivity oracles for graphs subject to vertex failures"
    - "multiple edge fault tolerant approximate shortest path trees"
    - "fully dynamic all pairs shortest paths with worst case update time revisited"

Connected through hyperedge HE-2 (induced by source paper "dynamic approximate shortest paths and beyond subquadratic and worst case update time"):
  with members:
    - "fully dynamic all pairs shortest paths improved worst case time and space bounds"
    - "dynamic matrix inverse improved algorithms and matching conditional lower bounds"
    - "towards tight approximation bounds for graph diameter and eccentricities"
    - "algorithms and hardness for diameter in dynamic graphs"
    - "diameter spanner eccentricity spanner and approximating extremal graph distances static dynamic and fault tolerant"
    - "a deamortization approach for dynamic spanner and dynamic maximal matching"
    - "deterministic partially dynamic single source shortest paths in weighted graphs"
    - "fully dynamic approximate maximum matching and minimum vertex cover in o log 3 n worst case update time"

Connected through hyperedge HE-3 (induced by source paper "dynamic matrix inverse improved algorithms and matching conditional lower bounds"):
  with members:
    - "dynamic approximate shortest paths and beyond subquadratic and worst case update time"
    - "a deterministic linear program solver in current matrix multiplication time"
    - "solving linear programs in the current matrix multiplication time"
    - "online bipartite matching with amortized o log 2 n replacements"
    - "tight cell probe bounds for succinct boolean matrix vector multiplication"
    - "improved rectangular matrix multiplication using powers of the coppersmith winograd tensor"
    - "dynamic minimum spanning forest with subpolynomial worst case update time"
    - "fully dynamic minimum spanning forest with improved worst case update time"

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)