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: "improving multivariate horner schemes with monte carlo tree search"
  Abstract: Abstract   Optimizing the cost of evaluating a polynomial is a classic problem in computer science. For polynomials in one variable, Horner’s method provides a scheme for producing a computationally efficient form. For multivariate polynomials it is possible to generalize Horner’s method, but this leaves freedom in the order of the variables. Traditionally, greedy schemes like most-occurring variable first are used. This simple textbook algorithm has given remarkably efficient results. Finding better algorithms has proved difficult. In trying to improve upon the greedy scheme we have implemented Monte Carlo tree search, a recent search method from the field of artificial intelligence. This results in better Horner schemes and reduces the cost of evaluating polynomials, sometimes by factors up to two.

Connected through hyperedge HE-1 (induced by source paper "scaling monte carlo tree search on intel xeon phi"):
  with members:
    - "performance analysis of a 240 thread tournament level mcts go program on the intel xeon phi"
    - "sss alpha beta tt"
    - "combining simulated annealing and monte carlo tree search for expression simplification"

Connected through hyperedge HE-2 (induced by source paper "ensemble uct needs high exploitation"):
  with members:
    - "performance analysis of a 240 thread tournament level mcts go program on the intel xeon phi"

Connected through hyperedge HE-3 (induced by source paper "hepgame and the simplification of expressions"):
  with members:
    - "form version 4 0"

Connected through hyperedge HE-4 (induced by source paper "code optimization in form"):
  with members:
    - "form version 4 0"

Connected through hyperedge HE-5 (induced by source paper "combining simulated annealing and monte carlo tree search for expression simplification"):
  with members:
    - "code optimization in form"

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)