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: "exact recovery of dirac ensembles from the projection onto spaces of spherical harmonics"
  Abstract: In this work we consider the problem of recovering an ensemble of Diracs on the sphere from its projection onto spaces of spherical harmonics. We show that under an appropriate separation condition on the unknown locations of the Diracs, the ensemble can be recovered through Total Variation norm minimization. The proof of the uniqueness of the solution uses the method of `dual' interpolating polynomials and is based on [8], where the theory was developed for trigonometric polynomials. We also show that in the special case of non-negative ensembles, a sparsity condition is sufficient for exact recovery.

Connected through hyperedge HE-1 (induced by source paper "stable support recovery of stream of pulses with application to ultrasound imaging"):
  with members:
    - "recovery of sparse positive signals on the sphere from low resolution measurements"
    - "super resolution on the sphere using convex optimization"
    - "sparse spikes deconvolution on thin grids"
    - "robust recovery of positive stream of pulses"
    - "robust recovery of stream of pulses using convex optimization"
    - "music for single snapshot spectral estimation stability and super resolution"
    - "exact recovery of non uniform splines from the projection onto spaces of algebraic polynomials"
    - "super resolution extremal functions and the condition number of vandermonde matrices"

Connected through hyperedge HE-2 (induced by source paper "adapting to unknown noise level in sparse deconvolution"):
  with members:
    - "support recovery for sparse deconvolution of positive measures"
    - "super resolution on the sphere using convex optimization"
    - "sparse spikes deconvolution on thin grids"
    - "robust recovery of stream of pulses using convex optimization"
    - "exact recovery of non uniform splines from the projection onto spaces of algebraic polynomials"
    - "near minimax line spectral estimation"
    - "support detection in super resolution"
    - "compressed sensing off the grid"

Connected through hyperedge HE-3 (induced by source paper "sampling sparse signals on the sphere algorithms and applications"):
  with members:
    - "super resolution on the sphere using convex optimization"
    - "an optimal dimensionality sampling scheme on the sphere with fast spherical harmonic transforms"
    - "towards a mathematical theory of super resolution"
    - "a novel sampling theorem on the sphere"

Connected through hyperedge HE-4 (induced by source paper "robust recovery of positive stream of pulses"):
  with members:
    - "compressive spectral estimation with single snapshot esprit stability and resolution"
    - "stable support recovery of stream of pulses with application to ultrasound imaging"
    - "music for multidimensional spectral estimation stability and super resolution"
    - "recovery of sparse positive signals on the sphere from low resolution measurements"
    - "super resolution of positive sources the discrete setup"
    - "support recovery for sparse deconvolution of positive measures"
    - "super resolution on the sphere using convex optimization"
    - "sparse spikes deconvolution on thin grids"

Connected through hyperedge HE-5 (induced by source paper "super resolution on the sphere using convex optimization"):
  with members:
    - "stable support recovery of stream of pulses with application to ultrasound imaging"
    - "robust recovery of stream of pulses using convex optimization"
    - "an optimal dimensionality sampling scheme on the sphere with fast spherical harmonic transforms"
    - "exact recovery of non uniform splines from the projection onto spaces of algebraic polynomials"
    - "super resolution extremal functions and the condition number of vandermonde matrices"
    - "near minimax line spectral estimation"
    - "sparse image reconstruction on the sphere implications of a new sampling theorem"
    - "precise semidefinite programming formulation of atomic norm minimization for recovering d dimensional d geq 2 off the grid frequencies"

Connected through hyperedge HE-6 (induced by source paper "recovery of sparse positive signals on the sphere from low resolution measurements"):
  with members:
    - "sampling sparse signals on the sphere algorithms and applications"
    - "stable support recovery of stream of pulses with application to ultrasound imaging"
    - "super resolution of positive sources the discrete setup"
    - "super resolution on the sphere using convex optimization"
    - "the recoverability limit for superresolution via sparsity"
    - "robust recovery of positive stream of pulses"
    - "robust recovery of stream of pulses using convex optimization"
    - "exact recovery of non uniform splines from the projection onto spaces of algebraic polynomials"

Connected through hyperedge HE-7 (induced by source paper "unified convex optimization approach to super resolution based on localized kernels"):
  with members:
    - "stable support recovery of stream of pulses with application to ultrasound imaging"
    - "super resolution on the sphere using convex optimization"
    - "robust recovery of positive stream of pulses"
    - "robust recovery of stream of pulses using convex optimization"
    - "music for single snapshot spectral estimation stability and super resolution"
    - "super resolution from short time fourier transform measurements"
    - "super resolution radar"
    - "exact recovery of non uniform splines from the projection onto spaces of algebraic polynomials"

Connected through hyperedge HE-8 (induced by source paper "exact solutions to super resolution on semi algebraic domains in higher dimensions"):
  with members:
    - "super resolution on the sphere using convex optimization"
    - "near minimax line spectral estimation"
    - "support detection in super resolution"
    - "towards a mathematical theory of super resolution"

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.IT(Information Theory)