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 "unified convex optimization approach to super resolution based on localized kernels"):
  Abstract: The problem of resolving the fine details of a signal from its coarse scale measurements or, as it is commonly referred to in the literature, the super-resolution problem arises naturally in engineering and physics in a variety of settings. We suggest a unified convex optimization approach for super-resolution. The key is the construction of an interpolating polynomial based on localized kernels. We also show that the localized kernels act as the connecting thread to another wide-spread problem of stream of pulses.

Includes members:
  Member "stable support recovery of stream of pulses with application to ultrasound imaging":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "stable super resolution of images a theoretical study")
  Member "super resolution on the sphere using convex optimization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "blind two dimensional super resolution and its performance guarantee")
  Member "robust recovery of positive stream of pulses":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "when does omp achieve support recovery with continuous dictionaries")
  Member "robust recovery of stream of pulses using convex optimization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the stable resolution limit of total variation regularization for spike deconvolution")
  Member "music for single snapshot spectral estimation stability and super resolution":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the stable resolution limit of total variation regularization for spike deconvolution")
  Member "super resolution from short time fourier transform measurements":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a theory of super resolution from short time fourier transform measurements")
  Member "super resolution radar":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "tree search network for sparse regression")
  Member "exact recovery of dirac ensembles from the projection onto spaces of spherical harmonics":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "stable support recovery of stream of pulses with application to ultrasound imaging")

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.IT(Information Theory)