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: "symmetric tensor decomposition"
  Abstract: We present an algorithm for decomposing a symmetric tensor, of dimension n and order d as a sum of rank-1 symmetric tensors, extending the algorithm of Sylvester devised in 1886 for binary forms. We recall the correspondence between the decomposition of a homogeneous polynomial in n variables of total degree d as a sum of powers of linear forms (Waring's problem), incidence properties on secant varieties of the Veronese Variety and the representation of linear forms as a linear combination of evaluations at distinct points. Then we reformulate Sylvester's approach from the dual point of view. Exploiting this duality, we propose necessary and sufficient conditions for the existence of such a decomposition of a given rank, using the properties of Hankel (and quasi-Hankel) matrices, derived from multivariate polynomials and normal form computations. This leads to the resolution of polynomial equations of small degree in non-generic cases. We propose a new algorithm for symmetric tensor decomposition, based on this characterization and on linear algebra computations with these Hankel matrices. The impact of this contribution is two-fold. First it permits an efficient computation of the decomposition of any tensor of sub-generic rank, as opposed to widely used iterative algorithms with unproved global convergence (e.g. Alternate Least Squares or gradient descents). Second, it gives tools for understanding uniqueness conditions, and for detecting the rank.

Connected through hyperedge HE-1 (induced by source paper "sparse interpolation in terms of multivariate chebyshev polynomials"):
  with members:
    - "sparse interpolation over finite fields via low order roots of unity"
    - "multivariate sparse interpolation using randomized kronecker substitutions"

Connected through hyperedge HE-2 (induced by source paper "derandomization and absolute reconstruction for sums of powers of linear forms"):
  with members:
    - "isomorphism problems for tensors groups and cubic forms completeness and reductions"
    - "orbits of monomials and factorization into products of linear forms"
    - "algorithms based on algebras and their applications to isomorphism of polynomials with one secret group isomorphism and polynomial identity testing"
    - "reconstruction algorithms for sums of affine powers"
    - "a deterministic polynomial time algorithm for non commutative rational identity testing"
    - "non commutative edmonds problem and matrix semi invariants"
    - "quasipolynomial time identity testing of non commutative and read once oblivious algebraic branching programs"

Connected through hyperedge HE-3 (induced by source paper "a nearly optimal algorithm to decompose binary forms"):
  with members:
    - "reconstruction algorithms for sums of affine powers"
    - "nearly optimal computations with structured matrices"

Connected through hyperedge HE-4 (induced by source paper "algorithms for zero dimensional ideals using linear recurrent sequences"):
  with members:
    - "sparse fglm algorithms"
    - "in depth comparison of the berlekamp massey sakata and the scalar fglm algorithms the non adaptive variants"
    - "polynomial systems solving by fast linear algebra"

Connected through hyperedge HE-5 (induced by source paper "in depth comparison of the berlekamp massey sakata and the scalar fglm algorithms the non adaptive variants"):
  with members:
    - "sparse fglm algorithms"

Connected through hyperedge HE-6 (induced by source paper "reconstruction algorithms for sums of affine powers"):
  with members:
    - "a nearly optimal algorithm to decompose binary forms"
    - "lower bounds by birkhoff interpolation"
    - "interpolation of shifted lacunary polynomials"

Connected through hyperedge HE-7 (induced by source paper "tensor factorization via matrix factorization"):
  with members:
    - "simultaneous diagonalization the asymmetric low rank and noisy settings"
    - "guaranteed non orthogonal tensor decomposition via alternating rank 1 updates"
    - "fast detection of overlapping communities via online tensor methods"
    - "unsupervised learning of noisy or bayesian networks"
    - "tensor decompositions for learning latent variable models"
    - "a method of moments for mixture models and hidden markov models"
    - "most tensor problems are np hard"

Connected through hyperedge HE-8 (induced by source paper "rank 1 tensor approximation methods and application to deflation"):
  with members:
    - "most tensor problems are np hard"

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)