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 "improving the numerical stability of fast matrix multiplication algorithms"):
  Abstract: Fast algorithms for matrix multiplication, or those that perform asymptotically fewer scalar operations than the classical algorithm, have been considered primarily of theoretical interest. Aside from Strassen's original algorithm, few fast algorithms have been efficiently implemented or used in practical applications. However, there exist many practical alternatives to Strassen's algorithm with varying performance and numerical properties. While fast algorithms are known to be numerically stable, their error bounds are slightly weaker than the classical algorithm. #R##N#We argue in this paper that the numerical sacrifice of fast algorithms, particularly for the typical use cases of practical algorithms, is not prohibitive, and we explore ways to improve the accuracy both theoretically and empirically. The numerical accuracy of fast matrix multiplication depends on properties of the algorithm and of the input matrices, and we consider both contributions independently. We generalize and tighten previous error analyses of fast algorithms, compare the properties among the class of known practical fast algorithms, and discuss algorithmic techniques for improving the error guarantees. We also present means for reducing the numerical inaccuracies generated by anomalous input matrices using diagonal scaling matrices. Finally, we include empirical results that test the various improvement techniques, in terms of both their numerical accuracy and their performance.

Includes members:
  Member "a framework for practical parallel fast matrix multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deterministic combinatorial replacement paths and distance sensitivity oracles")
  Member "powers of tensors and fast matrix multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "new lower bounds for the rank of matrix multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the complexity of matrix multiplication developments since 2014 extended abstract of 2018 oberwolfach complexity meeting plenary lecture")
  Member "communication optimal parallel algorithm for strassen s matrix multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "engineering boolean matrix multiplication for multiple accelerator shared memory architectures")

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.NA(Numerical Analysis)