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: "an improved randomized data structure for dynamic graph connectivity"
  Abstract: We present a randomized algorithm for dynamic graph connectivity. With failure probability less than $1/n^c$ (for any constant $c$ we choose), our solution has worst case running time $O(\log^3 n)$ per edge insertion, $O(\log^4 n)$ per edge deletion, and $O(\log n/\log\log n)$ per query, where $n$ is the number of vertices. The previous best algorithm has worst case running time $O(\log^4 n)$ per edge insertion and $O(\log^5 n)$ per edge deletion. The improvement is made by reducing the randomness used in the previous result, so that we save a $\log n$ factor in update time. #R##N#Specifically, \cite{kapron2013dynamic} uses $\log n$ copies of a data structure in order to boost a success probability from $1/2$ to $1-n^{-c}$. We show that, in fact though, because of the special structure of their algorithm, this boosting via repetition is unnecessary. Rather, we can still obtain the same correctness guarantee with high probability by arguing via a new invariant, without repetition.

Connected through hyperedge HE-1 (induced by source paper "approximate distance oracles subject to multiple vertex failures"):
  with members:
    - "sensitive distance and reachability oracles for large batch updates"
    - "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"

Connected through hyperedge HE-2 (induced by source paper "improved worst case deterministic parallel dynamic minimum spanning forest"):
  with members:
    - "dynamic minimum spanning forest with subpolynomial worst case update time"
    - "fully dynamic connectivity in o log n log log n 2 amortized expected time"
    - "fully dynamic minimum spanning forest with improved worst case update time"
    - "on fully dynamic graph sparsifiers"
    - "dynamic graph connectivity with improved worst case update time and sublinear space"
    - "faster worst case deterministic dynamic connectivity"
    - "faster fully dynamic minimum spanning forest"
    - "faster deterministic fully dynamic graph connectivity"

Connected through hyperedge HE-3 (induced by source paper "optimal lower bounds for universal relation and for samplers and finding duplicates in streams"):
  with members:
    - "optimal lower bounds for universal relation samplers and finding duplicates"
    - "on estimating maximum matching size in graph streams"
    - "densest subgraph in dynamic graph streams"
    - "dynamic graph connectivity with improved worst case update time and sublinear space"
    - "fast distributed algorithms for connectivity and mst in large graphs"
    - "sublinear estimation of weighted matchings in dynamic data streams"
    - "maximum matching in turnstile streams"
    - "space and time efficient algorithm for maintaining dense subgraphs on one pass dynamic streams"

Connected through hyperedge HE-4 (induced by source paper "optimal lower bounds for universal relation samplers and finding duplicates"):
  with members:
    - "on estimating maximum matching size in graph streams"
    - "densest subgraph in dynamic graph streams"
    - "dynamic graph connectivity with improved worst case update time and sublinear space"
    - "fast distributed algorithms for connectivity and mst in large graphs"
    - "sublinear estimation of weighted matchings in dynamic data streams"
    - "maximum matching in turnstile streams"

Connected through hyperedge HE-5 (induced by source paper "connectivity oracles for graphs subject to vertex failures"):
  with members:
    - "dynamic minimum spanning forest with subpolynomial worst case update time"
    - "improved algorithms for maintaining dfs tree in undirected graphs"
    - "fully dynamic connectivity in o log n log log n 2 amortized expected time"
    - "faster randomized worst case update time for dynamic subgraph connectivity"
    - "dynamic dfs in undirected graphs breaking the o m barrier"
    - "incremental and fully dynamic subgraph connectivity for emergency planning"
    - "faster online matrix vector multiplication"
    - "unifying and strengthening hardness for dynamic problems via the online matrix vector multiplication conjecture"

Connected through hyperedge HE-6 (induced by source paper "faster randomized worst case update time for dynamic subgraph connectivity"):
  with members:
    - "improved algorithms for maintaining dfs tree in undirected graphs"
    - "fully dynamic connectivity in o log n log log n 2 amortized expected time"
    - "dynamic dfs in undirected graphs breaking the o m barrier"
    - "fully dynamic minimum spanning forest with improved worst case update time"
    - "faster worst case update time for dynamic subgraph connectivity"
    - "unifying and strengthening hardness for dynamic problems via the online matrix vector multiplication conjecture"
    - "dynamic graph connectivity with improved worst case update time and sublinear space"
    - "faster worst case deterministic dynamic connectivity"

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)