human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "phasemax convex phase retrieval via basis pursuit"):
  Abstract: We consider the recovery of a (real- or complex-valued) signal from magnitude-only measurements, known as phase retrieval. We formulate phase retrieval as a convex optimization problem, which we call PhaseMax. Unlike other convex methods that use semidefinite relaxation and lift the phase retrieval problem to a higher dimension, PhaseMax is a "non-lifting" relaxation that operates in the original signal dimension. We show that the dual problem to PhaseMax is Basis Pursuit, which implies that phase retrieval can be performed using algorithms initially designed for sparse signal recovery. We develop sharp lower bounds on the success probability of PhaseMax for a broad range of random measurement ensembles, and we analyze the impact of measurement noise on the solution accuracy. We use numerical results to demonstrate the accuracy of our recovery guarantees, and we showcase the efficacy and limits of PhaseMax in practice.

Includes members:
  Member "phase retrieval via linear programming fundamental limits and algorithmic improvements":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "using black box compression algorithms for phase retrieval")
  Member "coordinate descent algorithms for phase retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "solving complex quadratic systems with full rank random matrices")
  Member "phase retrieval via reweighted wirtinger flow":
    also connected through other hyperedges:
      (none)
  Member "fundamental limits of phasemax for phase retrieval a replica analysis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "using black box compression algorithms for phase retrieval")
  Member "phase transitions of spectral initialization for high dimensional nonconvex estimation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a deterministic convergence framework for exact non convex phase retrieval")
  Member "branchhull convex bilinear inversion from the entrywise product of signals with known signs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "simultaneous structures in convex signal recovery revisiting the convex combination of norms")
  Member "non convex phase retrieval from stft measurements":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "toward a mathematical theory of the crystallographic phase retrieval problem")
  Member "corruption robust phase retrieval via linear programming":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "solving equations of random convex functions via anchored regression")

Question: Please tell me which class the source paper 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)