human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "matrox a model based algorithm with an efficient storage format for parallel hss structured matrix approximations"):
  Abstract: We present MatRox, a novel model-based algorithm and implementation of Hierarchically Semi-Separable (HSS) matrix computations on parallel architectures. MatRox uses a novel storage format to improve data locality and scalability of HSS matrix-matrix multiplications on shared memory multicore processors. We build a performance model for HSS matrix-matrix multiplications. Based on the performance model, a mixed-rank heuristic is introduced to find an optimal HSS-tree depth for a faster HSS matrix evaluation. Uniform sampling is used to improve the performance of HSS compression. MatRox outperforms state-of-the-art HSS matrix multiplication codes, GOFMM and STRUMPACK, with average speedups of 2.8x and 6.1x respectively on target multicore processors.

Includes members:
  Member "a study of clustering techniques and hierarchical matrix formats for kernel ridge regression":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "matrox modular approach for improving data locality in hierarchical mat rix app rox imation")
  Member "geometry oblivious fmm for compressing dense spd matrices":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "matrox modular approach for improving data locality in hierarchical mat rix app rox imation")
  Member "a fast block low rank dense solver with applications to finite element matrices":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "geostatistical modeling and prediction using mixed precision tile cholesky factorization")
  Member "a distributed memory package for dense hierarchically semi separable matrix computations using randomization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "matrox modular approach for improving data locality in hierarchical mat rix app rox imation")
  Member "uniform sampling for matrix approximation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sketching transformed matrices with applications to natural language processing")
  Member "askit approximate skeletonization kernel independent treecode in high dimensions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "matrox modular approach for improving data locality in hierarchical mat rix app rox imation")
  Member "revisiting the nystrom method for improved large scale machine learning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "approximating spectral clustering via sampling a review")
  Member "randomized algorithms for matrices and data":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "solving tall dense linear programs in nearly linear time")

Question: Please tell me which class the source paper 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)