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: "generalized preconditioning and network flow problems"
  Abstract: We consider approximation algorithms for the problem of finding $x$ of minimal norm $\|x\|$ satisfying a linear system $\mathbf{A} x = \mathbf{b}$, where the norm $\|\cdot \|$ is arbitrary and generally non-Euclidean. We show a simple general technique for composing solvers, converting iterative solvers with residual error $\|\mathbf{A} x - \mathbf{b}\| \leq t^{-\Omega(1)}$ into solvers with residual error $\exp(-\Omega(t))$, at the cost of an increase in $\|x\|$, by recursively invoking the solver on the residual problem $\tilde{\mathbf{b}} = \mathbf{b} - \mathbf{A} x$. Convergence of the composed solvers depends strongly on a generalization of the classical condition number to general norms, reducing the task of designing algorithms for many such problems to that of designing a \emph{generalized preconditioner} for $\mathbf{A}$. The new ideas significantly generalize those introduced by the author's earlier work on maximum flow, making them more widely applicable. #R##N#As an application of the new technique, we present a nearly-linear time approximation algorithm for uncapacitated minimum-cost flow on undirected graphs. Given an undirected graph with $m$ edges labelled with costs, and $n$ vertices labelled with demands, the algorithm takes $\epsilon^{-2}m^{1+o(1)}$-time and outputs a flow routing the demands with total cost at most $(1+\epsilon)$ times larger than minimal, along with a dual solution proving near-optimality. The generalized preconditioner is obtained by embedding the cost metric into $\ell_1$, and then considering a simple hierarchical routing scheme in $\ell_1$ where demands initially supported on a dense lattice are pulled from a sparser lattice by randomly rounding unaligned coordinates to their aligned neighbors. Analysis of the generalized condition number for the preconditioner follows that of the classical multigrid algorithm for lattice Laplacian systems.

Connected through hyperedge HE-1 (induced by source paper "near optimal approximate shortest paths and transshipment in distributed and streaming models"):
  with members:
    - "thorup zwick emulators are universally optimal hopsets"
    - "distributed exact shortest paths in sublinear time"
    - "improved distributed algorithms for exact shortest paths"
    - "further algebraic algorithms in the congested clique model and applications to graph theoretic problems"
    - "parallel shortest paths using radius stepping"
    - "a hierarchy of lower bounds for sublinear additive spanners"
    - "hopsets with constant hopbound and applications to approximate shortest paths"
    - "algebraic methods in the congested clique"

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)