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: "better late than never filling a void in the history of fast matrix multiplication and tensor decompositions"
  Abstract: Multilinear and tensor decompositions are a popular tool in linear and multilinear algebra and have a wide range of important applications to modern computing. Our paper of 1972 presented the first nontrivial application of such decompositions to fundamental matrix computations and was also a landmark in the history of the acceleration of matrix multiplication. Published in 1972 in Russian, it has never been translated into English. It has been very rarely cited in the Western literature on matrix multiplication and never in the works on multilinear and tensor decompositions. This motivates us to present its translation into English, together with our brief comments on its impact on the two fields.

Connected through hyperedge HE-1 (induced by source paper "strassen s 2x2 matrix multiplication algorithm a conceptual perspective"):
  with members:
    - "the geometry of rank decompositions of matrix multiplication ii 3 times 3 matrices"
    - "designing strassen s algorithm"
    - "generating families of practical fast matrix multiplication algorithms"
    - "matrix multiplication algorithms from group orbits"
    - "fast matrix multiplication and symbolic computation"
    - "powers of tensors and fast matrix multiplication"
    - "on symmetries of the strassen algorithm"

Connected through hyperedge HE-2 (induced by source paper "fast feasible and unfeasible matrix multiplication"):
  with members:
    - "hypergraph partitioning for sparse matrix matrix multiplication"
    - "exploiting multiple levels of parallelism in sparse matrix matrix multiplication"
    - "an improved combinatorial algorithm for boolean matrix multiplication"
    - "improving the numerical stability of fast matrix multiplication algorithms"
    - "a framework for practical parallel fast matrix multiplication"
    - "fast matrix multiplication limitations of the laser method"
    - "powers of tensors and fast matrix multiplication"
    - "nearly optimal computations with structured matrices"

Connected through hyperedge HE-3 (induced by source paper "matrix multiplication trilinear decompositions apa algorithms and summation"):
  with members:
    - "fast matrix multiplication limitations of the laser method"
    - "powers of tensors and fast matrix multiplication"
    - "faster algorithms for rectangular matrix multiplication"
    - "memory efficient scheduling of strassen winograd s matrix multiplication algorithm"
    - "all pairs shortest paths using bridging sets and rectangular matrix multiplication"

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.NA(Numerical Analysis)