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 "automatic generation of efficient linear algebra programs"):
  Abstract: The level of abstraction at which application experts reason about linear algebra computations and the level of abstraction used by developers of high-performance numerical linear algebra libraries do not match. The former is conveniently captured by high-level languages and libraries such as Matlab and Eigen, while the latter expresses the kernels included in the BLAS and LAPACK libraries. Unfortunately, the translation from a high-level computation to an efficient sequence of kernels is a task, far from trivial, that requires extensive knowledge of both linear algebra and high-performance computing. Internally, almost all high-level languages and libraries use efficient kernels; however, the translation algorithms are too simplistic and thus lead to a suboptimal use of said kernels, with significant performance losses. In order to both achieve the productivity that comes with high-level languages, and make use of the efficiency of low level kernels, we are developing Linnea, a code generator for linear algebra problems. As input, Linnea takes a high-level description of a linear algebra problem and produces as output an efficient sequence of calls to high-performance kernels. In 25 application problems, the code generated by Linnea always outperforms Matlab, Julia, Eigen and Armadillo, with speedups up to and exceeding 10x.

Includes members:
  Member "the generalized matrix chain algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "linnea automatic generation of efficient linear algebra programs")
  Member "non linear associative commutative many to one pattern matching with sequence variables":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "linnea automatic generation of efficient linear algebra programs")
  Member "efficient pattern matching in python":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "linnea automatic generation of efficient linear algebra programs")
  Member "image restoration by iterative denoising and backward projections":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a benchmark for sparse coding when group sparsity meets rank minimization")
  Member "matchpy a pattern matching library":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "linnea automatic generation of efficient linear algebra programs")
  Member "sparsity based correction of exponential artifacts":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "linnea automatic generation of efficient linear algebra programs")
  Member "a parallel implementation of the ensemble kalman filter based on modified cholesky decomposition":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "linnea automatic generation of efficient linear algebra programs")
  Member "on a natural dynamics for linear programming":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "linnea automatic generation of efficient linear algebra programs")

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.MS(Mathematical Software)