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: "cylindrical algebraic decomposition using local projections"
  Abstract: We present an algorithm which computes a cylindrical algebraic decomposition of a semialgebraic set using projection sets computed for each cell separately. Such local projection sets can be significantly smaller than the global projection set used by the Cylindrical Algebraic Decomposition (CAD) algorithm. This leads to reduction in the number of cells the algorithm needs to construct. We give an empirical comparison of our algorithm and the classical CAD algorithm.

Connected through hyperedge HE-1 (induced by source paper "cylindrical algebraic decomposition with equational constraints"):
  with members:
    - "identifying the parametric occurrence of multiple steady states for some biological networks"
    - "using machine learning to improve cylindrical algebraic decomposition"
    - "theoryguru a mathematica package to apply quantifier elimination technology to economics"
    - "non linear real arithmetic benchmarks derived from automated reasoning in economics"
    - "machine learning for mathematical software"
    - "towards incremental cylindrical algebraic decomposition in maple"
    - "symbolic versus numerical computation and visualization of parameter regions for multistationarity of biological networks"
    - "a case study on the parametric occurrence of multiple steady states"

Connected through hyperedge HE-2 (induced by source paper "using machine learning to improve cylindrical algebraic decomposition"):
  with members:
    - "machine learning for mathematical software"
    - "symbolic versus numerical computation and visualization of parameter regions for multistationarity of biological networks"
    - "a case study on the parametric occurrence of multiple steady states"
    - "need polynomial systems be doubly exponential"
    - "using machine learning to decide when to precondition cylindrical algebraic decomposition with groebner bases"
    - "truth table invariant cylindrical algebraic decomposition"
    - "the complexity of cylindrical algebraic decomposition with respect to polynomial degree"
    - "improving the use of equational constraints in cylindrical algebraic decomposition"

Connected through hyperedge HE-3 (induced by source paper "comparing machine learning models to choose the variable ordering for cylindrical algebraic decomposition"):
  with members:
    - "using machine learning to improve cylindrical algebraic decomposition"
    - "theoryguru a mathematica package to apply quantifier elimination technology to economics"
    - "non linear real arithmetic benchmarks derived from automated reasoning in economics"
    - "machine learning for mathematical software"
    - "symbolic versus numerical computation and visualization of parameter regions for multistationarity of biological networks"
    - "a case study on the parametric occurrence of multiple steady states"
    - "deepmath deep sequence models for premise selection"
    - "using machine learning to decide when to precondition cylindrical algebraic decomposition with groebner bases"

Connected through hyperedge HE-4 (induced by source paper "theoryguru a mathematica package to apply quantifier elimination technology to economics"):
  with members:
    - "non linear real arithmetic benchmarks derived from automated reasoning in economics"
    - "a case study on the parametric occurrence of multiple steady states"
    - "applying machine learning to the problem of choosing a heuristic to select the variable ordering for cylindrical algebraic decomposition"
    - "computing equilibria of semi algebraic economies using triangular decomposition and real solution classification"

Connected through hyperedge HE-5 (induced by source paper "cad adjacency computation using validated numerics"):
  with members:
    - "divide and conquer computation of cylindrical algebraic decomposition"
    - "computing cylindrical algebraic decomposition via triangular decomposition"

Connected through hyperedge HE-6 (induced by source paper "truth table invariant cylindrical algebraic decomposition"):
  with members:
    - "improving the use of equational constraints in cylindrical algebraic decomposition"
    - "truth table invariant cylindrical algebraic decomposition by regular chains"
    - "applying machine learning to the problem of choosing a heuristic to select the variable ordering for cylindrical algebraic decomposition"
    - "choosing a variable ordering for truth table invariant cylindrical algebraic decomposition by incremental triangular decomposition"
    - "using the distribution of cells by dimension in a cylindrical algebraic decomposition"
    - "problem formulation for truth table invariant cylindrical algebraic decomposition by incremental triangular decomposition"
    - "using the regular chains library to build cylindrical algebraic decompositions by projecting and lifting"
    - "cylindrical algebraic sub decompositions"

Connected through hyperedge HE-7 (induced by source paper "experience with heuristics benchmarks standards for cylindrical algebraic decomposition"):
  with members:
    - "need polynomial systems be doubly exponential"
    - "using machine learning to decide when to precondition cylindrical algebraic decomposition with groebner bases"
    - "truth table invariant cylindrical algebraic decomposition"
    - "the complexity of cylindrical algebraic decomposition with respect to polynomial degree"
    - "improving the use of equational constraints in cylindrical algebraic decomposition"
    - "a comparison of three heuristics to choose the variable ordering for cylindrical algebraic decomposition"
    - "truth table invariant cylindrical algebraic decomposition by regular chains"
    - "applying machine learning to the problem of choosing a heuristic to select the variable ordering for cylindrical algebraic decomposition"

Connected through hyperedge HE-8 (induced by source paper "the complexity of cylindrical algebraic decomposition with respect to polynomial degree"):
  with members:
    - "need polynomial systems be doubly exponential"
    - "using machine learning to decide when to precondition cylindrical algebraic decomposition with groebner bases"
    - "truth table invariant cylindrical algebraic decomposition"
    - "improving the use of equational constraints in cylindrical algebraic decomposition"
    - "truth table invariant cylindrical algebraic decomposition by regular chains"
    - "applying machine learning to the problem of choosing a heuristic to select the variable ordering for cylindrical algebraic decomposition"
    - "using the distribution of cells by dimension in a cylindrical algebraic decomposition"
    - "problem formulation for truth table invariant cylindrical algebraic decomposition by incremental triangular decomposition"

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)