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 from multiple window short time fourier measurements"
  Abstract: In this paper, we introduce two undirected graphs depending on supports of signals and windows, and we show that the connectivity of those graphs provides either necessary or sufficient conditions to phase retrieval of a signal from magnitude measurements of its multiple-window short-time Fourier transform. Also, we propose an algebraic reconstruction algorithm, and provide an error estimate to our algorithm when magnitude measurements are corrupted by deterministic/random noises.

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"
    - "phaseless sampling and reconstruction of real valued signals in shift invariant spaces"
    - "shift invariant and sampling spaces associated with the special affine fourier transform"
    - "phase retrieval of real valued signals in a shift invariant space"
    - "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 "generalized haar condition based phaseless random sampling for compactly supported functions in shift invariant spaces"):
  with members:
    - "measurement matrix design for phase retrieval based on mutual information"
    - "phaseless sampling and reconstruction of real valued signals in shift invariant spaces"

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 the magnitudes of affine linear measurements"
    - "corruption robust phase retrieval via linear programming"
    - "phase retrieval of real valued signals in a shift invariant space"
    - "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"

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)