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: "fast matrix multiplication and symbolic computation"
  Abstract: The complexity of matrix multiplication (hereafter MM) has been intensively studied since 1969, when Strassen surprisingly decreased the exponent 3 in the cubic cost of the straightforward classical MM to log 2 (7) ≈ 2.8074. Applications to some fundamental problems of Linear Algebra and Computer Science have been immediately recognized, but the researchers in Computer Algebra keep discovering more and more applications even today, with no sign of slowdown. We survey the unfinished history of decreasing the exponent towards its information lower bound 2, recall some important techniques discovered in this process and linked to other fields of computing, reveal sample surprising applications to fast computation of the inner products of two vectors and summation of integers, and discuss the curse of recursion, which separates the progress in fast MM into its most acclaimed and purely theoretical part and into valuable acceleration of MM of feasible sizes. Then, in the second part of our paper, we cover fast MM in realistic symbolic computations and discuss applications and implementation of fast exact matrix multiplication. We first review how most of exact linear algebra can be reduced to matrix multiplication over small finite fields. Then we highlight the differences in the design of approximate and exact implementations of fast MM, taking into account nowadays processor and memory hierarchies. In the concluding section we comment on current perspectives of the study of fast MM.

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"
    - "powers of tensors and fast matrix multiplication"
    - "on symmetries of the strassen algorithm"
    - "better late than never filling a void in the history of fast matrix multiplication and tensor decompositions"

Connected through hyperedge HE-2 (induced by source paper "laderman matrix multiplication algorithm can be constructed using strassen algorithm and related tensor s isotropies"):
  with members:
    - "the geometry of rank decompositions of matrix multiplication i 2x2 matrices"
    - "matrix multiplication algorithms from group orbits"
    - "symmetries of matrix multiplication algorithms i"
    - "fast matrix multiplication limitations of the laser method"
    - "a new general purpose method to multiply 3x3 matrices using only 23 multiplications"

Connected through hyperedge HE-3 (induced by source paper "a non commutative algorithm for multiplying 5 5 matrices using 99 multiplications"):
  with members:
    - "laderman matrix multiplication algorithm can be constructed using strassen algorithm and related tensor s isotropies"
    - "a framework for practical parallel fast 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.SC(Symbolic Computation)