human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "output sensitive algorithms for sumset and sparse polynomial multiplication"):
  Abstract: We present randomized algorithms to compute the sumset (Minkowski sum) of two integer sets, and to multiply two univariate integer polynomials given by sparse representations. Our algorithm for sumset has cost softly linear in the combined size of the inputs and output. This is used as part of our sparse multiplication algorithm, whose cost is softly linear in the combined size of the inputs, output, and the sumset of the supports of the inputs. As a subroutine, we present a new method for computing the coefficients of a sparse polynomial, given a set containing its support. Our multiplication algorithm extends to multivariate Laurent polynomials over finite fields and rational numbers. Our techniques are based on sparse interpolation algorithms and results from analytic number theory.

Includes members:
  Member "sparse interpolation over finite fields via low order roots of unity":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sparse interpolation in terms of multivariate chebyshev polynomials")
  Member "faster sparse multivariate polynomial interpolation of straight line programs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "sparse polynomial interpolation based on diversification")
  Member "faster polynomial multiplication over finite fields":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "generic reductions for in place polynomial multiplication")
  Member "even faster integer multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the i o complexity of hybrid algorithms for integer multiplication")
  Member "highly scalable multiplication for distributed sparse multivariate polynomials on many core systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the parallelization of triangular decomposition of polynomial systems")
  Member "chunky and equal spaced polynomial multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "essentially optimal sparse polynomial multiplication")
  Member "interpolation of shifted lacunary polynomials":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "what can and can t we do with sparse polynomials")

Question: Please tell me which class the source paper 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)