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: "a new algorithm for decremental single source shortest paths with applications to vertex capacitated flow and cut problems"
  Abstract: We study the vertex-decremental Single-Source Shortest Paths (SSSP) problem: given an undirected graph $G=(V,E)$ with lengths $\ell(e)\geq 1$ on its edges and a source vertex $s$, we need to support (approximate) shortest-path queries in $G$, as $G$ undergoes vertex deletions. In a shortest-path query, given a vertex $v$, we need to return a path connecting $s$ to $v$, whose length is at most $(1+\epsilon)$ times the length of the shortest such path, where $\epsilon$ is a given accuracy parameter. The problem has many applications, for example to flow and cut problems in vertex-capacitated graphs. #R##N#Our main result is a randomized algorithm for vertex-decremental SSSP with total expected update time $O(n^{2+o(1)}\log L)$, that responds to each shortest-path query in $O(n\log L)$ time in expectation, returning a $(1+\epsilon)$-approximate shortest path. The algorithm works against an adaptive adversary. The main technical ingredient of our algorithm is an $\tilde O(|E(G)|+ n^{1+o(1)})$-time algorithm to compute a \emph{core decomposition} of a given dense graph $G$, which allows us to compute short paths between pairs of query vertices in $G$ efficiently. We believe that this core decomposition algorithm may be of independent interest. We use our result for vertex-decremental SSSP to obtain $(1+\epsilon)$-approximation algorithms for maximum $s$-$t$ flow and minimum $s$-$t$ cut in vertex-capacitated graphs, in expected time $n^{2+o(1)}$, and an $O(\log^4n)$-approximation algorithm for the vertex version of the sparsest cut problem with expected running time $n^{2+o(1)}$. These results improve upon the previous best known results for these problems in the regime where $m= \omega(n^{1.5 + o(1)})$.

Connected through hyperedge HE-1 (induced by source paper "a deterministic algorithm for balanced cut with applications to dynamic connectivity flows and beyond"):
  with members:
    - "faster p norm minimizing flows via smoothed q norm problems"
    - "fast provably convergent irls algorithm for p norm linear regression"
    - "distributed edge connectivity in sublinear time"
    - "improved distributed expander decomposition and nearly optimal triangle enumeration"
    - "flows in almost linear time via adaptive preconditioning"
    - "breaking quadratic time for small vertex connectivity and an approximation scheme"
    - "graph sparsification spectral sketches and faster resistance computation via short cycle decompositions"
    - "short cycles via low diameter decompositions"

Connected through hyperedge HE-2 (induced by source paper "rounding dynamic matchings against an adaptive adversary"):
  with members:
    - "decremental sssp in weighted digraphs faster and against an adaptive adversary"
    - "deterministic algorithms for decremental approximate shortest paths faster and simpler"
    - "tight bounds for online edge coloring"
    - "distributed weighted matching via randomized composable coresets"
    - "online matching with general arrivals"
    - "dynamic low stretch trees via dynamic low diameter decompositions"
    - "towards a unified theory of sparsification for matching problems"
    - "reoptimization via gradual transformations"

Connected through hyperedge HE-3 (induced by source paper "a new deterministic algorithm for dynamic set cover"):
  with members:
    - "dynamic matrix inverse improved algorithms and matching conditional lower bounds"
    - "breaking quadratic time for small vertex connectivity and an approximation scheme"
    - "a deamortization approach for dynamic spanner and dynamic maximal matching"
    - "fully dynamic approximate maximum matching and minimum vertex cover in o log 3 n worst case update time"
    - "dynamic minimum spanning forest with subpolynomial worst case update time"
    - "deterministic fully dynamic approximate vertex cover and fractional matching in o 1 amortized update time"
    - "fully dynamic maximal matching in constant update time"
    - "new deterministic approximation algorithms for fully dynamic matching"

Connected through hyperedge HE-4 (induced by source paper "computing and testing small connectivity in near linear time and queries via fast local cut algorithms"):
  with members:
    - "a faster local algorithm for detecting bounded size cuts with applications to higher connectivity problems"
    - "computing and testing small vertex connectivity in near linear time and queries"
    - "breaking quadratic time for small vertex connectivity and an approximation scheme"
    - "expander decomposition and pruning faster stronger and simpler"
    - "faster algorithms for computing maximal 2 connected subgraphs in sparse directed graphs"
    - "on sampling edges almost uniformly"
    - "local flow partitioning for faster edge connectivity"
    - "on fully dynamic graph sparsifiers"

Connected through hyperedge HE-5 (induced by source paper "breaking quadratic time for small vertex connectivity and an approximation scheme"):
  with members:
    - "expander decomposition and pruning faster stronger and simpler"
    - "capacity releasing diffusion for speed and locality"
    - "local flow partitioning for faster edge connectivity"
    - "dynamic minimum spanning forest with subpolynomial worst case update time"
    - "a simple and strongly local flow based method for cut improvement"
    - "fully dynamic minimum spanning forest with improved worst case update time"
    - "deterministic global minimum cut of a simple graph in near linear time"
    - "flow based algorithms for local graph clustering"

Connected through hyperedge HE-6 (induced by source paper "computing and testing small vertex connectivity in near linear time and queries"):
  with members:
    - "a faster local algorithm for detecting bounded size cuts with applications to higher connectivity problems"
    - "breaking quadratic time for small vertex connectivity and an approximation scheme"
    - "faster algorithms for computing maximal 2 connected subgraphs in sparse directed graphs"
    - "distributed connectivity decomposition"

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)