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: "symmetries of matrix multiplication algorithms i"
  Abstract: In this work the algorithms of fast multiplication of matrices are considered. To any algorithm there associated a certain group of automorphisms. These automorphism groups are found for some well-known algorithms, including algorithms of Hopcroft, Laderman, and Pan. The automorphism group is isomorphic to $S_3\times Z_2$ and $S_4$ for Hopcroft anf Laderman algorithms, respectively. The studying of symmetry of algorithms may be a fruitful idea for finding fast algorithms, by an analogy with well-known optimization problems for codes, lattices, and graphs. #R##N#{\em Keywords}: Strassen algorithm, symmetry, fast matrix multiplication.

Connected through hyperedge HE-1 (induced by source paper "designing strassen s algorithm"):
  with members:
    - "strassen s 2x2 matrix multiplication algorithm a conceptual perspective"
    - "the geometry of rank decompositions of matrix multiplication i 2x2 matrices"
    - "matrix multiplication algorithms from group orbits"
    - "on the geometry of border rank algorithms for n x 2 by 2 x 2 matrix multiplication"
    - "powers of tensors and fast matrix multiplication"
    - "on symmetries of the strassen algorithm"
    - "new lower bounds for the rank of matrix multiplication"
    - "geometric complexity theory and tensor rank"

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"
    - "fast matrix multiplication and symbolic computation"
    - "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 "matrix multiplication algorithms from group orbits"):
  with members:
    - "the geometry of rank decompositions of matrix multiplication i 2x2 matrices"
    - "a 2n 2 log n 1 lower bound for the border rank of matrix multiplication"
    - "on the geometry of border rank algorithms for n x 2 by 2 x 2 matrix multiplication"
    - "fast matrix multiplication limitations of the laser method"
    - "powers of tensors and fast matrix multiplication"
    - "on symmetries of the strassen algorithm"
    - "equations for lower bounds on border rank"
    - "new lower bounds for the rank of 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.CC(Computational Complexity)