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: "approaching optimality for solving sdd systems"
  Abstract: We present an algorithm that on input of an $n$-vertex $m$-edge weighted graph $G$ and a value $k$, produces an {\em incremental sparsifier} $\hat{G}$ with $n-1 + m/k$ edges, such that the condition number of $G$ with $\hat{G}$ is bounded above by $\tilde{O}(k\log^2 n)$, with probability $1-p$. The algorithm runs in time #R##N#$$\tilde{O}((m \log{n} + n\log^2{n})\log(1/p)).$$ #R##N#As a result, we obtain an algorithm that on input of an $n\times n$ symmetric diagonally dominant matrix $A$ with $m$ non-zero entries and a vector $b$, computes a vector ${x}$ satisfying $||{x}-A^{+}b||_A<\epsilon ||A^{+}b||_A $, in expected time #R##N#$$\tilde{O}(m\log^2{n}\log(1/\epsilon)).$$ #R##N#The solver is based on repeated applications of the incremental sparsifier that produces a chain of graphs which is then used as input to a recursive preconditioned Chebyshev iteration.

Connected through hyperedge HE-1 (induced by source paper "solving linear programs with sqrt rank linear system solves"):
  with members:
    - "solving linear programs in the current matrix multiplication time"
    - "approximate gaussian elimination for laplacians fast sparse and simple"
    - "sparsified cholesky and multigrid solvers for connection laplacians"
    - "sparsified cholesky solvers for sdd linear systems"
    - "efficient inverse maintenance and faster algorithms for linear programming"
    - "sketching as a tool for numerical linear algebra"
    - "uniform sampling for matrix approximation"
    - "an efficient parallel solver for sdd linear systems"

Connected through hyperedge HE-2 (induced by source paper "high precision estimation of random walks in small space"):
  with members:
    - "deterministic approximation of random walks in small space"
    - "solving directed laplacian systems in nearly linear time through sparse lu factorizations"
    - "derandomization beyond connectivity undirected laplacian systems in nearly logarithmic space"
    - "faster algorithms for computing the stationary distribution simulating random walks and more"
    - "approximate gaussian elimination for laplacians fast sparse and simple"
    - "almost linear time algorithms for markov chains and new spectral primitives for directed graphs"
    - "sparsified cholesky and multigrid solvers for connection laplacians"
    - "spectral sparsification of random walk matrix polynomials"

Connected through hyperedge HE-3 (induced by source paper "derandomization beyond connectivity undirected laplacian systems in nearly logarithmic space"):
  with members:
    - "faster algorithms for computing the stationary distribution simulating random walks and more"
    - "almost linear time algorithms for markov chains and new spectral primitives for directed graphs"
    - "efficient inverse maintenance and faster algorithms for linear programming"
    - "pseudorandomness and fourier growth bounds for width 3 branching programs"
    - "an almost linear time algorithm for approximate max flow in undirected graphs and its multicommodity generalizations"
    - "an efficient parallel solver for sdd linear systems"
    - "pseudorandomness for regular branching programs via fourier analysis"
    - "efficient accelerated coordinate descent methods and faster algorithms for solving linear systems"

Connected through hyperedge HE-4 (induced by source paper "matrix scaling and balancing via box constrained newton s method and interior point methods"):
  with members:
    - "an sdp based algorithm for linear sized spectral sparsification"
    - "much faster algorithms for matrix scaling"
    - "approximate gaussian elimination for laplacians fast sparse and simple"
    - "sparsified cholesky and multigrid solvers for connection laplacians"
    - "constructing linear sized spectral sparsification in almost linear time"
    - "sparsified cholesky solvers for sdd linear systems"
    - "faster parametric shortest path and minimum balance algorithms"
    - "analysis of a classical matrix preconditioning algorithm"

Connected through hyperedge HE-5 (induced by source paper "sparse sums of positive semidefinite matrices"):
  with members:
    - "a matrix hyperbolic cosine algorithm and applications"
    - "faster spectral sparsification and numerical algorithms for sdd matrices"
    - "a parallel approximation algorithm for positive semidefinite programming"
    - "near optimal column based matrix reconstruction"
    - "graph sparsification by edge connectivity and random spanning trees"
    - "towards an sdp based approach to spectral methods a nearly linear time algorithm for graph partitioning and decomposition"
    - "a linear time algorithm for sparsification of unweighted graphs"
    - "graph sparsification via refinement sampling"

Connected through hyperedge HE-6 (induced by source paper "computing maximum flow with augmenting electrical flows"):
  with members:
    - "approximate gaussian elimination for laplacians fast sparse and simple"
    - "sparsified cholesky and multigrid solvers for connection laplacians"
    - "approximate undirected maximum flows in o m polylog n time"
    - "an almost linear time algorithm for approximate max flow in undirected graphs and its multicommodity generalizations"
    - "a simple combinatorial algorithm for solving sdd systems in nearly linear time"
    - "navigating central path with electrical flows from flows to matchings and back"
    - "nearly maximum flows in nearly linear time"
    - "a nearly mlogn time solver for sdd linear systems"

Connected through hyperedge HE-7 (induced by source paper "an empirical study of cycle toggling based laplacian solvers"):
  with members:
    - "is nearly linear the same in theory and practice a case study with a combinatorial laplacian solver"
    - "fast provable algorithms for isotonic regression in all ell_ p norms"
    - "efficient accelerated coordinate descent methods and faster algorithms for solving linear systems"
    - "a simple combinatorial algorithm for solving sdd systems in nearly linear time"
    - "runtime guarantees for regression problems"
    - "nearly linear time algorithms for preconditioning and solving symmetric diagonally dominant linear systems"
    - "benchmarking optimization software with performance profiles"

Connected through hyperedge HE-8 (induced by source paper "fast generation of random spanning trees and the effective resistance metric"):
  with members:
    - "an almost linear time algorithm for approximate max flow in undirected graphs and its multicommodity generalizations"
    - "a simple combinatorial algorithm for solving sdd systems in nearly linear time"
    - "navigating central path with electrical flows from flows to matchings and back"
    - "nearly maximum flows in nearly linear time"
    - "a nearly mlogn time solver for sdd linear systems"
    - "fast approximation algorithms for cut based problems in undirected graphs"
    - "electrical flows laplacian systems and faster approximation of maximum flow in undirected graphs"
    - "faster generation of random spanning trees"

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)