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: "on the uniqueness of frog methods"
  Abstract: The problem of recovering a signal from its power spectrum, called  phase retrieval , arises in many scientific fields. One of many examples is ultrashort laser pulse characterization, in which the electromagnetic field is oscillating with   $\sim{\text{10}}^{15}$   Hz and phase information cannot be measured directly due to limitations of the electronic sensors. Phase retrieval is ill-posed in most of the cases, as there are many different signals with the same Fourier transform magnitude. To overcome this fundamental ill-posedness, several measurement techniques are used in practice. One of the most popular methods for complete characterization of ultrashort laser pulses is the frequency-resolved optical gating (FROG). In FROG, the acquired data are the power spectrum of the product of the unknown pulse with its delayed replica. Therefore, the measured signal is a quartic function of the unknown pulse. A generalized version of FROG, where the delayed replica is replaced by a second unknown pulse, is called blind FROG. In this case, the measured signal is quadratic with respect to both pulses. In this letter, we introduce and formulate FROG-type techniques. We then show that almost all band-limited signals are determined uniquely, up to trivial ambiguities, by blind FROG measurements (and thus also by FROG), if in addition we have access to the signals power spectrum.

Connected through hyperedge HE-1 (induced by source paper "toward a mathematical theory of the crystallographic phase retrieval problem"):
  with members:
    - "a note on douglas rachford subgradients and phase retrieval"
    - "phase retrieval for binary signals box relaxation and uniqueness"
    - "learning without loss"
    - "single particle cryo electron microscopy mathematical theory computational challenges and opportunities"
    - "blind phaseless short time fourier transform recovery"
    - "on signal reconstruction from frog measurements"
    - "fourier phase retrieval uniqueness and algorithms"
    - "structured signal recovery from quadratic measurements breaking sample complexity barriers via nonconvex optimization"

Connected through hyperedge HE-2 (induced by source paper "blind phaseless short time fourier transform recovery"):
  with members:
    - "multi target detection with application to cryo electron microscopy"
    - "toward single particle reconstruction without particle picking breaking the detection limit"
    - "blind deconvolutional phase retrieval via convex programming"
    - "bispectrum inversion with application to multireference alignment"
    - "on signal reconstruction from frog measurements"
    - "stable blind deconvolution over the reals from additional autocorrelations"
    - "fourier phase retrieval uniqueness and algorithms"
    - "blind deconvolution with additional autocorrelations via convex programs"

Connected through hyperedge HE-3 (induced by source paper "bispectrum inversion with application to multireference alignment"):
  with members:
    - "message passing algorithms for synchronization problems over compact groups"
    - "on signal reconstruction from frog measurements"
    - "fourier phase retrieval uniqueness and algorithms"
    - "the sample complexity of multi reference alignment"
    - "non convex phase retrieval from stft measurements"
    - "the projected power method an efficient algorithm for joint alignment from pairwise differences"
    - "fundamental limits in multi image alignment"
    - "near optimal joint object matching via convex relaxation"

Connected through hyperedge HE-4 (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"
    - "improved recovery guarantees for phase retrieval from coded diffraction patterns"
    - "multireference alignment is easier with an aperiodic translation distribution"

Connected through hyperedge HE-5 (induced by source paper "on signal reconstruction from frog measurements"):
  with members:
    - "bispectrum inversion with application to multireference alignment"
    - "fourier phase retrieval uniqueness and algorithms"
    - "benchmark problems for phase retrieval"
    - "non convex phase retrieval from stft measurements"
    - "stft phase retrieval uniqueness guarantees and recovery algorithms"
    - "a geometric analysis of phase retrieval"
    - "solving random quadratic systems of equations is nearly as easy as solving linear systems"
    - "phase retrieval via wirtinger flow theory and algorithms"

Connected through hyperedge HE-6 (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"
    - "improved recovery guarantees for phase retrieval from coded diffraction patterns"
    - "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)