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: "robust recovery of positive stream of pulses"
  Abstract: The problem of estimating the delays and amplitudes of a positive stream of pulses appears in many applications, such as single-molecule microscopy. This paper suggests estimating the delays and amplitudes using a convex program, which is robust in the presence of noise (or model mismatch). Particularly, the recovery error is proportional to the noise level. We further show that the error grows exponentially with the density of the delays and also depends on the localization properties of the pulse.

Connected through hyperedge HE-1 (induced by source paper "when does omp achieve support recovery with continuous dictionaries"):
  with members:
    - "a sharp restricted isometry constant bound of orthogonal matching pursuit"
    - "super resolution of positive sources the discrete setup"
    - "an improved rip based performance guarantee for sparse signal recovery via orthogonal matching pursuit"
    - "a remark on the restricted isometry property in orthogonal matching pursuit"
    - "towards a mathematical theory of super resolution"
    - "improved rip analysis of orthogonal matching pursuit"
    - "sparse recovery with orthogonal matching pursuit under rip"
    - "learning gaussian mixtures with arbitrary separation"

Connected through hyperedge HE-2 (induced by source paper "fourier phase retrieval uniqueness and algorithms"):
  with members:
    - "message passing algorithms for synchronization problems over compact groups"
    - "bispectrum inversion with application to multireference alignment"
    - "on fienup methods for sparse phase retrieval"
    - "on signal reconstruction from frog measurements"
    - "on the 2d phase retrieval problem"
    - "multiple illumination phaseless super resolution mips with applications to phaseless doa estimation and diffraction imaging"
    - "on the uniqueness of frog methods"
    - "improved recovery guarantees for phase retrieval from coded diffraction patterns"

Connected through hyperedge HE-3 (induced by source paper "non convex phase retrieval from stft measurements"):
  with members:
    - "message passing algorithms for synchronization problems over compact groups"
    - "bispectrum inversion with application to multireference alignment"
    - "on fienup methods for sparse phase retrieval"
    - "on signal reconstruction from frog measurements"
    - "fourier phase retrieval uniqueness and algorithms"
    - "on the uniqueness of frog methods"
    - "improved recovery guarantees for phase retrieval from coded diffraction patterns"
    - "stft phase retrieval uniqueness guarantees and recovery algorithms"

Connected through hyperedge HE-4 (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 stream of pulses using convex optimization"
    - "music for single snapshot spectral estimation stability and super resolution"
    - "exact recovery of dirac ensembles from the projection onto spaces of spherical harmonics"
    - "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-5 (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 stream of pulses using convex optimization"
    - "exact recovery of dirac ensembles from the projection onto spaces of spherical harmonics"
    - "exact recovery of non uniform splines from the projection onto spaces of algebraic polynomials"

Connected through hyperedge HE-6 (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 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 dirac ensembles from the projection onto spaces of spherical harmonics"
    - "exact recovery of non uniform splines from the projection onto spaces of algebraic polynomials"

Connected through hyperedge HE-7 (induced by source paper "robust recovery of stream of pulses using convex optimization"):
  with members:
    - "stable support recovery of stream of pulses with application to ultrasound imaging"
    - "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"
    - "exact solutions to super resolution on semi algebraic domains in higher dimensions"
    - "spectral super resolution with prior knowledge"
    - "music for single snapshot spectral estimation stability and super resolution"
    - "exact recovery of dirac ensembles from the projection onto spaces of spherical harmonics"

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)