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 fast distributed solver for symmetric diagonally dominant linear equations"
  Abstract: In this paper, we propose a fast distributed solver for linear equations given by symmetric diagonally dominant M-Matrices. Our approach is based on a distributed implementation of the parallel solver of Spielman and Peng by considering a specific approximated inverse chain which can be computed efficiently in a distributed fashion. Representing the system of equations by a graph $\mathbb{G}$, the proposed distributed algorithm is capable of attaining $\epsilon$-close solutions (for arbitrary $\epsilon$) in time proportional to $n^{3}$ (number of nodes in $\mathbb{G}$), ${\alpha}$ (upper bound on the size of the R-Hop neighborhood), and $\frac{{W}_{max}}{{W}_{min}}$ (maximum and minimum weight of edges in $\mathbb{G}$).

Connected through hyperedge HE-1 (induced by source paper "a distributed laplacian solver and its applications to electrical flow and random spanning tree computation"):
  with members:
    - "current flow group closeness centrality for complex networks"
    - "pooling or sampling collective dynamics for electrical flow estimation"
    - "an almost linear time algorithm for uniform random spanning tree generation"
    - "decentralized random walk based data collection in networks"
    - "sampling random spanning trees faster than matrix multiplication"
    - "estimating current flow closeness centrality with a multigrid laplacian solver"
    - "computing maximum flow with augmenting electrical flows"
    - "fast generation of random spanning trees and the effective resistance metric"

Connected through hyperedge HE-2 (induced by source paper "caddelag framework for distributed anomaly detection in large dense graph sequences"):
  with members:
    - "matrix computations and optimization in apache spark"
    - "powers of tensors and fast matrix multiplication"
    - "graph based anomaly detection and description a survey"
    - "deltacon a principled massive graph similarity function"
    - "large scale spectral clustering using resistance distance and spielman teng solvers"
    - "nearly linear time algorithms for preconditioning and solving symmetric diagonally dominant linear systems"

Connected through hyperedge HE-3 (induced by source paper "network flows that solve linear equations"):
  with members:
    - "decentralized gradient algorithm for solution of a linear equation"
    - "a distributed algorithm for solving a linear algebraic equation"
    - "solving systems of linear equations locally and asynchronously"
    - "distributed strongly convex optimization"
    - "fast distributed gradient methods"
    - "cooperative convex optimization in networked systems augmented lagrangian algorithms with directed gossip communication"
    - "randomized optimal consensus of multi agent systems"
    - "reaching an optimal consensus dynamical systems that compute intersections of convex sets"

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.DC(Distributed, Parallel, and Cluster Computing)