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: "triangular decomposition of semi algebraic systems"
  Abstract: Regular chains and triangular decompositions are fundamental and well-developed tools for describing the complex solutions of polynomial systems. This paper proposes adaptations of these tools focusing on solutions of the real analogue: semi-algebraic systems. We show that any such system can be decomposed into finitely many {\em regular semi-algebraic systems}. We propose two specifications of such a decomposition and present corresponding algorithms. Under some assumptions, one type of decomposition can be computed in singly exponential time w.r.t.\ the number of variables. We implement our algorithms and the experimental results illustrate their effectiveness.

Connected through hyperedge HE-1 (induced by source paper "smooth points on semi algebraic sets"):
  with members:
    - "computing the homology of basic semialgebraic sets in weak exponential time"
    - "certifying solutions to overdetermined and singular polynomial systems over q"
    - "a probabilistic algorithm to compute the real dimension of a semi algebraic set"

Connected through hyperedge HE-2 (induced by source paper "identifying the parametric occurrence of multiple steady states for some biological networks"):
  with members:
    - "using machine learning to improve cylindrical algebraic decomposition"
    - "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"
    - "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"
    - "applying machine learning to the problem of choosing a heuristic to select the variable ordering for cylindrical algebraic decomposition"

Connected through hyperedge HE-3 (induced by source paper "visualizing planar and space implicit real algebraic curves with singularities"):
  with members:
    - "complete subdivision algorithms ii isotopic meshing of singular algebraic curves"

Connected through hyperedge HE-4 (induced by source paper "computing elimination ideals and discriminants of likelihood equations"):
  with members:
    - "data discriminants of likelihood equations"
    - "special algorithm for stability analysis of multistable biological regulatory systems"
    - "solution regions in the parameter space of a 3 rrr decoupled robot for a prescribed workspace"

Connected through hyperedge HE-5 (induced by source paper "positive solutions of systems of signed parametric polynomial inequalities"):
  with members:
    - "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"
    - "subtropical real root finding"

Connected through hyperedge HE-6 (induced by source paper "symbolic versus numerical computation and visualization of parameter regions for multistationarity of biological networks"):
  with members:
    - "a case study on the parametric occurrence of multiple steady states"
    - "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"
    - "computing cylindrical algebraic decomposition via triangular decomposition"

Connected through hyperedge HE-7 (induced by source paper "a case study on the parametric occurrence of multiple steady states"):
  with members:
    - "the complexity of cylindrical algebraic decomposition with respect to polynomial degree"
    - "improving the use of equational constraints in cylindrical algebraic decomposition"
    - "computing cylindrical algebraic decomposition via triangular decomposition"

Connected through hyperedge HE-8 (induced by source paper "a probabilistic algorithm for computing data discriminants of likelihood equations"):
  with members:
    - "data discriminants of likelihood equations"
    - "probabilistic algorithm for polynomial optimization over a real algebraic set"

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)