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: "phase retrieval with application to optical imaging"
  Abstract: This review article provides a contemporary overview of phase retrieval in optical imaging, linking the relevant optical physics to the signal processing methods and algorithms. Our goal is to describe the current state of the art in this area, identify challenges, and suggest future directions and areas where signal processing methods can have a large impact on optical imaging and on the world of imaging at large with applications in a variety of fields ranging from biology and chemistry to physics and engineering.

Connected through hyperedge HE-1 (induced by source paper "phase retrieval without small ball probability assumptions"):
  with members:
    - "improved recovery guarantees for phase retrieval from coded diffraction patterns"
    - "robust nonnegative sparse recovery and the nullspace property of 0 1 measurements"
    - "a partial derandomization of phaselift using spherical designs"
    - "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-2 (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"
    - "improved recovery guarantees for phase retrieval from coded diffraction patterns"
    - "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"

Connected through hyperedge HE-3 (induced by source paper "low rank phase retrieval"):
  with members:
    - "scalable solvers of random quadratic equations via stochastic truncated amplitude flow"
    - "correlated pca principal components analysis when data and noise are correlated"
    - "solving random quadratic systems of equations is nearly as easy as solving linear systems"
    - "phase retrieval via wirtinger flow theory and algorithms"
    - "fast matrix completion without the condition number"
    - "gespar efficient phase retrieval of sparse signals"
    - "phase retrieval stability and recovery guarantees"
    - "recursive robust pca or recursive sparse recovery in large but structured noise"

Connected through hyperedge HE-4 (induced by source paper "multiple illumination phaseless super resolution mips with applications to phaseless doa estimation and diffraction imaging"):
  with members:
    - "efficient compressive phase retrieval with constrained sensing vectors"
    - "phase retrieval an overview of recent developments"
    - "phase retrieval from coded diffraction patterns"
    - "sparse phase retrieval convex algorithms and limitations"
    - "simultaneously structured models with application to sparse and low rank matrices"
    - "compressed sensing off the grid"
    - "towards a mathematical theory of super resolution"
    - "phaselift exact and stable signal recovery from magnitude measurements via convex programming"

Connected through hyperedge HE-5 (induced by source paper "coordinate descent algorithms for phase retrieval"):
  with members:
    - "stft phase retrieval uniqueness guarantees and recovery algorithms"
    - "solving random quadratic systems of equations is nearly as easy as solving linear systems"
    - "phase retrieval via wirtinger flow theory and algorithms"
    - "gespar efficient phase retrieval of sparse signals"
    - "phase retrieval from coded diffraction patterns"
    - "phaselift exact and stable signal recovery from magnitude measurements via convex programming"
    - "phase retrieval via matrix completion"

Connected through hyperedge HE-6 (induced by source paper "stft phase retrieval uniqueness guarantees and recovery algorithms"):
  with members:
    - "improved recovery guarantees for phase retrieval from coded diffraction patterns"
    - "compressive phase retrieval via generalized approximate message passing"
    - "phase retrieval an overview of recent developments"
    - "sparse phase retrieval from short time fourier measurements"
    - "quadratic basis pursuit"
    - "phase retrieval for sparse signals uniqueness conditions"
    - "gespar efficient phase retrieval of sparse signals"
    - "phase retrieval from coded diffraction patterns"

Connected through hyperedge HE-7 (induced by source paper "reconstruction of signals from their autocorrelation and cross correlation vectors with applications to phase retrieval and blind channel estimation"):
  with members:
    - "on the 2d phase retrieval problem"
    - "stft phase retrieval uniqueness guarantees and recovery algorithms"
    - "phasemax convex phase retrieval via basis pursuit"
    - "an elementary proof of convex phase retrieval in the natural parameter space via the linear program phasemax"
    - "phase retrieval meets statistical learning theory a flexible convex relaxation"
    - "convex recovery of a structured signal from independent random linear measurements"
    - "phase retrieval via wirtinger flow theory and algorithms"
    - "phase retrieval an overview of recent developments"

Connected through hyperedge HE-8 (induced by source paper "solving random quadratic systems of equations is nearly as easy as solving linear systems"):
  with members:
    - "improved recovery guarantees for phase retrieval from coded diffraction patterns"
    - "guaranteed matrix completion via non convex factorization"
    - "simple efficient and neural algorithms for sparse coding"
    - "a partial derandomization of phaselift using spherical designs"
    - "compressive phase retrieval via generalized approximate message passing"
    - "complete dictionary recovery over the sphere"
    - "efficient compressive phase retrieval with constrained sensing vectors"
    - "phase retrieval via wirtinger flow theory and algorithms"

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)