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: "computing popov and hermite forms of rectangular polynomial matrices"
  Abstract: We consider the computation of two normal forms for matrices over the univariate polynomials: the Popov form and the Hermite form. For matrices which are square and nonsingular, deterministic algorithms with satisfactory cost bounds are known. Here, we present deterministic, fast algorithms for rectangular input matrices. The obtained cost bound for the Popov form matches the previous best known randomized algorithm, while the cost bound for the Hermite form improves on the previous best known ones by a factor which is at least the largest dimension of the input matrix.

Connected through hyperedge HE-1 (induced by source paper "implementations of efficient univariate polynomial matrix algorithms and application to bivariate resultants"):
  with members:
    - "fast computation of approximant bases in canonical form"
    - "block krylov techniques in the context of sparse fglm algorithms"
    - "improved rectangular matrix multiplication using powers of the coppersmith winograd tensor"
    - "fast computation of minimal interpolation bases in popov form for arbitrary shifts"
    - "fast deterministic computation of the hermite normal form and determinant of a polynomial matrix"
    - "sub quadratic decoding of one point hermitian codes"
    - "computing minimal interpolation bases"
    - "faster arithmetic for number theoretic transforms"

Connected through hyperedge HE-2 (induced by source paper "interactive certificates for polynomial matrices with sub linear communication"):
  with members:
    - "computing canonical bases of modules of univariate relations"
    - "fast deterministic computation of the hermite normal form and determinant of a polynomial matrix"
    - "powers of tensors and 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)