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: "detecting lacunary perfect powers and computing their roots"
  Abstract: We consider solutions to the equation f = h^r for polynomials f and h and integer r > 1. Given a polynomial f in the lacunary (also called sparse or super-sparse) representation, we first show how to determine if f can be written as h^r and, if so, to find such an r. This is a Monte Carlo randomized algorithm whose cost is polynomial in the number of non-zero terms of f and in log(deg f), i.e., polynomial in the size of the lacunary representation, and it works over GF(q)[x] (for large characteristic) as well as Q[x]. We also give two deterministic algorithms to compute the perfect root h given f and r. The first is output-sensitive (based on the sparsity of h) and works only over Q[x]. A sparsity-sensitive Newton iteration forms the basis for the second approach to computing h, which is extremely efficient and works over both GF(q)[x] (for large characteristic) and Q[x], but depends on a number-theoretic conjecture. Work of Erdos, Schinzel, Zannier, and others suggests that both of these algorithms are unconditionally polynomial-time in the lacunary size of the input polynomial f. Finally, we demonstrate the efficiency of the randomized detection algorithm and the latter perfect root computation algorithm with an implementation in the C++ library NTL.

Connected through hyperedge HE-1 (induced by source paper "what can and can t we do with sparse polynomials"):
  with members:
    - "bounded degree factors of lacunary multivariate polynomials"
    - "output sensitive algorithms for sumset and sparse polynomial multiplication"
    - "parallel sparse interpolation using small primes"
    - "sparse interpolation over finite fields via low order roots of unity"
    - "faster sparse multivariate polynomial interpolation of straight line programs"
    - "faster polynomial multiplication over finite fields"
    - "multivariate sparse interpolation using randomized kronecker substitutions"
    - "faster sparse interpolation of straight line programs"

Connected through hyperedge HE-2 (induced by source paper "computing the multilinear factors of lacunary polynomials without heights"):
  with members:
    - "pseudorandomness for multilinear read once algebraic branching programs in any order"
    - "factoring bivariate lacunary polynomials without heights"
    - "a wronskian approach to the real tau conjecture"
    - "the limited power of powering polynomial identity testing and a depth four lower bound for the permanent"

Connected through hyperedge HE-3 (induced by source paper "factoring bivariate lacunary polynomials without heights"):
  with members:
    - "a wronskian approach to the real tau conjecture"

Connected through hyperedge HE-4 (induced by source paper "diversification improves interpolation"):
  with members:
    - "progress on polynomial identity testing ii"

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)