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: "dynamic effective resistances and approximate schur complement on separable graphs"
  Abstract: We consider the problem of dynamically maintaining (approximate) all-pairs effective resistances in separable graphs, which are those that contain small balanced separators. We give a fully dynamic algorithm that maintains $(1+\varepsilon)$-approximations of the all-pairs effective resistances of an $n$-vertex graph $G$ undergoing edge insertions and deletions with $\tilde{O}(\sqrt{n}/\varepsilon^2)$ worst-case update time and $\tilde{O}(\sqrt{n}/\varepsilon^2)$ worst-case query time, if $G$ is guaranteed to be $O(\sqrt{n})$-separable (i.e., admit a balanced separator of size $O(\sqrt{n})$) and its separator can be computed in $\tilde{O}(n)$ time. Our algorithm is built upon a dynamic algorithm for maintaining \emph{approximate Schur complement} that approximately preserves pairwise effective resistances among a set of terminals for separable graphs, which might be of independent interest. #R##N#We also show that our algorithm is close to optimal by proving that for any two fixed vertices $s$ and $t$, there is no incremental or decremental (and thus, also no fully dynamic) algorithm that $(1+O(\frac{1}{n^{36}}))$-approximates the $s-t$ effective resistance for $O(\sqrt{n})$-separable graphs with worst-case update time $O(n^{1/2-\delta})$ and query time $O(n^{1-\delta})$ for any $\delta>0$, unless the Online Matrix Vector Multiplication (OMv) conjecture is false. #R##N#We further show that for \emph{general} graphs, no incremental or decremental algorithm can maintain a $(1+O(\frac{1}{n^{20}}))$-approximation of the $s-t$ effective resistance with worst-case update time $O(n^{1-\delta})$ and query-time $O(n^{2-\delta})$ for any $\delta >0$, unless the OMv conjecture is false.

Connected through hyperedge HE-1 (induced by source paper "fully dynamic spectral vertex sparsifiers and applications"):
  with members:
    - "dynamic low stretch trees via dynamic low diameter decompositions"
    - "graph reduction by local variation"
    - "kirchhoff index as a measure of edge centrality in weighted networks nearly linear time algorithms"
    - "on solving linear systems in sublinear time"
    - "spectrally approximating large graphs with smaller graphs"
    - "an almost linear time algorithm for uniform random spanning tree generation"
    - "density independent algorithms for sparsifying k step random walks"
    - "the power of vertex sparsifiers in dynamic graph algorithms"

Connected through hyperedge HE-2 (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"
    - "breaking quadratic time for small vertex connectivity and an approximation scheme"
    - "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-3 (induced by source paper "spectral subspace sparsification"):
  with members:
    - "an almost linear time algorithm for uniform random spanning tree generation"
    - "improved guarantees for vertex sparsification in planar graphs"
    - "determinant preserving sparsification of sddm matrices with applications to counting and sampling spanning trees"
    - "sampling random spanning trees faster than matrix multiplication"
    - "graph minors for preserving terminal distances approximately lower and upper bounds"
    - "approximate gaussian elimination for laplacians fast sparse and simple"
    - "vertex sparsifiers new results from old techniques"
    - "approximate maximum flow on separable undirected graphs"

Connected through hyperedge HE-4 (induced by source paper "optimal offline dynamic 2 3 edge vertex connectivity"):
  with members:
    - "fully dynamic spectral vertex sparsifiers and applications"
    - "maximizing the number of spanning trees in a connected graph"
    - "kirchhoff index as a measure of edge centrality in weighted networks nearly linear time algorithms"
    - "dynamic bridge finding in tilde o log 2 n amortized time"
    - "the power of vertex sparsifiers in dynamic graph algorithms"
    - "fully dynamic connectivity in o log n log log n 2 amortized expected time"
    - "sampling random spanning trees faster than matrix multiplication"
    - "on the hardness of partially dynamic graph problems and connections to diameter"

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)