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 via structured modulations in paley wiener spaces"
  Abstract: This paper considers the recovery of continuous time signals from the magnitude of its samples. It uses a combination of structured modulation and oversampling and provides sufficient conditions on the signal and the sampling system such that signal recovery is possible. In particular, it is shown that an average sampling rate of four times the Nyquist rate is sufficient to reconstruct a signal from its magnitude measurements.

Connected through hyperedge HE-1 (induced by source paper "phase retrieval of real valued signals in a shift invariant space"):
  with members:
    - "phaseless sampling and reconstruction of real valued signals in shift invariant spaces"
    - "phase retrieval from the magnitudes of affine linear measurements"
    - "prime phase retrieval via majorization minimization"
    - "nonlinear frames and sparse reconstructions in banach spaces"
    - "spatially distributed sampling and reconstruction"
    - "phase retrieval via wirtinger flow theory and algorithms"
    - "phase retrieval an overview of recent developments"
    - "phasecode fast and efficient compressive phase retrieval based on sparse graph codes"

Connected through hyperedge HE-2 (induced by source paper "system approximations and generalized measurements in modern sampling theory"):
  with members:
    - "signal and system approximation from general measurements"
    - "phaseless signal recovery in infinite dimensional spaces using structured modulations"
    - "phase retrieval from low rate samples"
    - "the papr problem in ofdm transmission new directions for a long lasting problem"
    - "phaselift exact and stable signal recovery from magnitude measurements via convex programming"
    - "phase retrieval via matrix completion"
    - "recovering signals from lowpass data"
    - "beyond bandlimited sampling nonlinearities smoothness and sparsity"

Connected through hyperedge HE-3 (induced by source paper "compressive phase retrieval of sparse bandlimited signals"):
  with members:
    - "compressive phase retrieval via generalized approximate message passing"
    - "sparse signal recovery from quadratic measurements via convex programming"
    - "phase retrieval via matrix completion"
    - "beyond nyquist efficient sampling of sparse bandlimited signals"
    - "from theory to practice sub nyquist sampling of sparse wideband analog signals"

Connected through hyperedge HE-4 (induced by source paper "fast compressive phase retrieval from fourier measurements"):
  with members:
    - "a partial derandomization of phaselift using spherical designs"
    - "compressive phase retrieval via generalized approximate message passing"
    - "phasecode fast and efficient compressive phase retrieval based on sparse graph codes"
    - "phaseless signal recovery in infinite dimensional spaces using structured modulations"
    - "new conditions for sparse phase retrieval"
    - "phase retrieval from low rate samples"
    - "phase retrieval from coded diffraction patterns"
    - "sparse signal recovery from quadratic measurements via convex programming"

Connected through hyperedge HE-5 (induced by source paper "phase retrieval from low rate samples"):
  with members:
    - "a partial derandomization of phaselift using spherical designs"
    - "phaseless signal recovery in infinite dimensional spaces using structured modulations"
    - "phase retrieval from coded diffraction patterns"
    - "solving quadratic equations via phaselift when there are about as many equations as unknowns"
    - "phase retrieval with polarization"
    - "phaselift exact and stable signal recovery from magnitude measurements via convex programming"
    - "phase retrieval via matrix completion"
    - "the power of convex relaxation near optimal matrix completion"

Connected through hyperedge HE-6 (induced by source paper "phaseless signal recovery in infinite dimensional spaces using structured modulations"):
  with members:
    - "phase retrieval from low rate samples"
    - "phase retrieval via matrix completion"

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)