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 of real valued signals in a shift invariant space"
  Abstract: Phase retrieval arises in various fields of science and engineering and it is well studied in a finite-dimensional setting. In this paper, we consider an infinite-dimensional phase retrieval problem to reconstruct real-valued signals living in a shift-invariant space from its phaseless samples taken either on the whole line or on a set with finite sampling rate. We find the equivalence between nonseparability of signals in a linear space and its phase retrievability with phaseless samples taken on the whole line. For a spline signal of order $N$, we show that it can be well approximated, up to a sign, from its noisy phaseless samples taken on a set with sampling rate $2N-1$. We propose an algorithm to reconstruct nonseparable signals in a shift-invariant space generated by a compactly supported continuous function. The proposed algorithm is robust against bounded sampling noise and it could be implemented in a distributed manner.

Connected through hyperedge HE-1 (induced by source paper "random phaseless sampling for causal signals in shift invariant spaces a zero distribution perspective"):
  with members:
    - "measurement matrix design for phase retrieval based on mutual information"
    - "phase retrieval from multiple window short time fourier measurements"
    - "phaseless sampling and reconstruction of real valued signals in shift invariant spaces"
    - "shift invariant and sampling spaces associated with the special affine fourier transform"
    - "phaselift exact and stable signal recovery from magnitude measurements via convex programming"
    - "phase retrieval via matrix completion"

Connected through hyperedge HE-2 (induced by source paper "stable phaseless sampling and reconstruction of real valued signals with finite rate of innovations"):
  with members:
    - "phaseless sampling and reconstruction of real valued signals in shift invariant spaces"
    - "spatially distributed sampling and reconstruction"
    - "phase retrieval an overview of recent developments"
    - "phase retrieval for sparse signals"
    - "phaselift exact and stable signal recovery from magnitude measurements via convex programming"
    - "phase retrieval via matrix completion"

Connected through hyperedge HE-3 (induced by source paper "phaseless sampling and reconstruction of real valued signals in shift invariant spaces"):
  with members:
    - "phase retrieval from multiple window short time fourier measurements"
    - "phase retrieval from the magnitudes of affine linear measurements"
    - "corruption robust phase retrieval via linear programming"
    - "spatially distributed sampling and reconstruction"
    - "phase retrieval an overview of recent developments"
    - "phaseless signal recovery in infinite dimensional spaces using structured modulations"
    - "phase retrieval from low rate samples"
    - "phaselift exact and stable signal recovery from magnitude measurements via convex programming"

Connected through hyperedge HE-4 (induced by source paper "phase retrieval from multiple window short time fourier measurements"):
  with members:
    - "stft phase retrieval uniqueness guarantees and recovery algorithms"
    - "a least squares approach for stable phase retrieval from short time fourier transform magnitude"
    - "phase retrieval an overview of recent developments"
    - "sparse phase retrieval from short time fourier measurements"
    - "phase retrieval from coded diffraction patterns"
    - "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)