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: "polynomial systems solving by fast linear algebra"
  Abstract: Polynomial system solving is a classical problem in mathematics with a wide range of applications. This makes its complexity a fundamental problem in computer science. Depending on the context, solving has different meanings. In order to stick to the most general case, we consider a representation of the solutions from which one can easily recover the exact solutions or a certified approximation of them. Under generic assumption, such a representation is given by the lexicographical Grobner basis of the system and consists of a set of univariate polynomials. The best known algorithm for computing the lexicographical Grobner basis is in $\widetilde{O}(d^{3n})$ arithmetic operations where $n$ is the number of variables and $d$ is the maximal degree of the equations in the input system. The notation $\widetilde{O}$ means that we neglect polynomial factors in $n$. We show that this complexity can be decreased to $\widetilde{O}(d^{\omega n})$ where $2 \leq \omega < 2.3727$ is the exponent in the complexity of multiplying two dense matrices. Consequently, when the input polynomial system is either generic or reaches the Bezout bound, the complexity of solving a polynomial system is decreased from $\widetilde{O}(D^3)$ to $\widetilde{O}(D^\omega)$ where $D$ is the number of solutions of the system. To achieve this result we propose new algorithms which rely on fast linear algebra. When the degree of the equations are bounded uniformly by a constant we propose a deterministic algorithm. In the unbounded case we present a Las Vegas algorithm.

Connected through hyperedge HE-1 (induced by source paper "gr o bner basis over semigroup algebras algorithms and applications for sparse polynomial systems"):
  with members:
    - "on the chordality of polynomial sets in triangular decomposition in top down style"
    - "exploiting chordal structure in polynomial ideals a grobner bases approach"
    - "sparse grobner bases the unmixed case"

Connected through hyperedge HE-2 (induced by source paper "computing syzygies in finite dimension using fast linear algebra"):
  with members:
    - "fast computation of approximant bases in canonical form"
    - "fast computation of minimal interpolation bases in popov form for arbitrary shifts"
    - "computing minimal interpolation bases"

Connected through hyperedge HE-3 (induced by source paper "block krylov techniques in the context of sparse fglm algorithms"):
  with members:
    - "algorithms for zero dimensional ideals using linear recurrent sequences"
    - "sparse fglm algorithms"
    - "fast computation of minimal interpolation bases in popov form for arbitrary shifts"
    - "on the complexity of the generalized minrank problem"

Connected through hyperedge HE-4 (induced by source paper "algorithms for zero dimensional ideals using linear recurrent sequences"):
  with members:
    - "sparse fglm algorithms"
    - "in depth comparison of the berlekamp massey sakata and the scalar fglm algorithms the non adaptive variants"
    - "symmetric tensor decomposition"

Connected through hyperedge HE-5 (induced by source paper "exploiting chordal structure in polynomial ideals a grobner bases approach"):
  with members:
    - "sparse grobner bases the unmixed case"
    - "gr obner bases and nullstellens atze for graph coloring ideals"

Connected through hyperedge HE-6 (induced by source paper "on the p adic stability of the fglm algorithm"):
  with members:
    - "matrix f5 algorithms over finite precision complete discrete valuation fields"

Connected through hyperedge HE-7 (induced by source paper "real root finding for low rank linear matrices"):
  with members:
    - "sparse fglm algorithms"
    - "determinantal sets singularities and application to optimal control in medical imagery"
    - "bit complexity for multi homogeneous polynomial system solving application to polynomial minimization"
    - "real root finding for rank defects in linear hankel matrices"
    - "real root finding for determinants of linear matrices"
    - "a nearly optimal algorithm for deciding connectivity queries in smooth and bounded real algebraic sets"
    - "probabilistic algorithm for polynomial optimization over a real algebraic set"
    - "critical points and gr obner bases the unmixed case"

Connected through hyperedge HE-8 (induced by source paper "random sampling in computational algebra helly numbers and violator spaces"):
  with members:
    - "exploiting chordal structure in polynomial ideals a grobner bases approach"
    - "sparse grobner bases the unmixed case"
    - "gr obner bases and nullstellens atze for graph coloring ideals"
    - "clarksons algorithm for violator spaces"
    - "violator spaces structure and algorithms"

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)