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: "improved recovery guarantees for phase retrieval from coded diffraction patterns"
  Abstract: Abstract   In this work we analyze the problem of phase retrieval from Fourier measurements with random diffraction patterns. To this end, we consider the recently introduced PhaseLift algorithm, which expresses the problem in the language of convex optimization. We provide recovery guarantees which require    O  (    log    2    ⁡  d  )    different diffraction patterns, thus improving on recent results by Candes et al.  [1] , which demand    O  (    log    4    ⁡  d  )    different patterns.

Connected through hyperedge HE-1 (induced by source paper "complex phase retrieval from subgaussian measurements"):
  with members:
    - "on the convex geometry of blind deconvolution and matrix completion"
    - "phase retrieval without small ball probability assumptions"
    - "structured signal recovery from quadratic measurements breaking sample complexity barriers via nonconvex optimization"
    - "phasemax convex phase retrieval via basis pursuit"
    - "a geometric analysis of phase retrieval"
    - "phase retrieval meets statistical learning theory a flexible convex relaxation"
    - "stable low rank matrix recovery via null space properties"
    - "solving random quadratic systems of equations is nearly as easy as solving linear systems"

Connected through hyperedge HE-2 (induced by source paper "alternating phase projected gradient descent with generative priors for solving compressive phase retrieval"):
  with members:
    - "phase retrieval under a generative prior"
    - "robust compressive phase retrieval via deep generative priors"
    - "began boundary equilibrium generative adversarial networks"
    - "image restoration by iterative denoising and backward projections"
    - "learning deep cnn denoiser prior for image restoration"
    - "sparse phase retrieval via truncated amplitude flow"
    - "unsupervised representation learning with deep convolutional generative adversarial networks"
    - "solving random quadratic systems of equations is nearly as easy as solving linear systems"

Connected through hyperedge HE-3 (induced by source paper "phase retrieval without small ball probability assumptions"):
  with members:
    - "robust nonnegative sparse recovery and the nullspace property of 0 1 measurements"
    - "a partial derandomization of phaselift using spherical designs"
    - "phase retrieval with application to optical imaging"
    - "low rank matrix recovery from rank one measurements"
    - "phase retrieval from coded diffraction patterns"
    - "phase retrieval stability and recovery guarantees"
    - "one bit compressed sensing with non gaussian measurements"
    - "solving quadratic equations via phaselift when there are about as many equations as unknowns"

Connected through hyperedge HE-4 (induced by source paper "structured signal recovery from quadratic measurements breaking sample complexity barriers via nonconvex optimization"):
  with members:
    - "multiple illumination phaseless super resolution mips with applications to phaseless doa estimation and diffraction imaging"
    - "sparse phase retrieval via truncated amplitude flow"
    - "non convex phase retrieval from stft measurements"
    - "reconstruction of signals from their autocorrelation and cross correlation vectors with applications to phase retrieval and blind channel estimation"
    - "stft phase retrieval uniqueness guarantees and recovery algorithms"
    - "compressed sensing from phaseless gaussian measurements via linear programming in the natural parameter space"
    - "phasemax convex phase retrieval via basis pursuit"
    - "rapid robust and reliable blind deconvolution via nonconvex optimization"

Connected through hyperedge HE-5 (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"
    - "multireference alignment is easier with an aperiodic translation distribution"

Connected through hyperedge HE-6 (induced by source paper "stable blind deconvolution over the reals from additional autocorrelations"):
  with members:
    - "blind demixing and deconvolution at near optimal rate"
    - "reconstruction of signals from their autocorrelation and cross correlation vectors with applications to phase retrieval and blind channel estimation"
    - "explicit frames for deterministic phase retrieval via phaselift"
    - "rapid robust and reliable blind deconvolution via nonconvex optimization"
    - "sparse model uncertainties in compressed sensing with application to convolutions and sporadic communication"
    - "on the stability of sparse convolutions"
    - "fundamental limits of blind deconvolution part i ambiguity kernel"
    - "blind deconvolution using convex programming"

Connected through hyperedge HE-7 (induced by source paper "on the uniqueness of frog methods"):
  with members:
    - "non convex phase retrieval from stft measurements"
    - "stft phase retrieval uniqueness guarantees and recovery algorithms"
    - "phase retrieval via wirtinger flow theory and algorithms"
    - "phase retrieval an overview of recent developments"
    - "sparse phase retrieval from short time fourier measurements"
    - "phase retrieval for sparse signals uniqueness conditions"
    - "gespar efficient phase retrieval of sparse signals"
    - "phase retrieval from coded diffraction patterns"

Connected through hyperedge HE-8 (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"
    - "stft phase retrieval uniqueness guarantees and recovery algorithms"
    - "the projected power method an efficient algorithm for joint alignment from pairwise differences"

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)