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: "fast algorithms for spherical harmonic expansions"
  Abstract: We provide an efficient algorithm for calculating, at appropriately chosen points on the two-dimensional surface of the unit sphere in R^3, the values of functions that are specified by their spherical harmonic expansions (a procedure known as the inverse spherical harmonic transform). We also provide an efficient algorithm for calculating the coefficients in the spherical harmonic expansions of functions that are specified by their values at these appropriately chosen points (a procedure known as the forward spherical harmonic transform). The algorithms are numerically stable, and, if the number of points in our standard tensor-product discretization of the surface of the sphere is proportional to l^2, then the algorithms have costs proportional to l^2ln(l) at any fixed precision of computations. Several numerical examples illustrate the performance of the algorithms.

Connected through hyperedge HE-1 (induced by source paper "warped convolutions efficient invariance to spatial transformations"):
  with members:
    - "learning rotation invariant convolutional filters for texture classification"
    - "group equivariant convolutional networks"
    - "spatial transformer networks"
    - "fast algorithms for convolutional neural networks"
    - "adam a method for stochastic optimization"
    - "locally scale invariant convolutional neural networks"
    - "semantic image segmentation with deep convolutional nets and fully connected crfs"
    - "matconvnet convolutional neural networks for matlab"

Connected through hyperedge HE-2 (induced by source paper "an efficient hybrid tridiagonal divide and conquer algorithm on distributed memory architectures"):
  with members:
    - "new fast divide and conquer algorithms for the symmetric tridiagonal eigenvalue problem"
    - "a distributed memory package for dense hierarchically semi separable matrix computations using randomization"

Connected through hyperedge HE-3 (induced by source paper "fast steerable principal component analysis"):
  with members:
    - "orthogonal matrix retrieval in cryo electron microscopy"
    - "fourier bessel rotational invariant eigenimages"

Connected through hyperedge HE-4 (induced by source paper "parallel spherical harmonic transforms on heterogeneous architectures gpus multi core cpus"):
  with members:
    - "spherical harmonic transform with gpus"

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.NA(Numerical Analysis)