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 "sublinear time algorithms for compressive phase retrieval"):
  Abstract: In the compressive phase retrieval problem, or phaseless compressed sensing, or compressed sensing from intensity only measurements, the goal is to reconstruct a sparse or approximately $k$-sparse vector $x \in \mathbb{R}^n$ given access to $y= |\Phi x|$, where $|v|$ denotes the vector obtained from taking the absolute value of $v\in\mathbb{R}^n$ coordinate-wise. In this paper we present sublinear-time algorithms for different variants of the compressive phase retrieval problem which are akin to the variants considered for the classical compressive sensing problem in theoretical computer science. Our algorithms use pure combinatorial techniques and near-optimal number of measurements.

Includes members:
  Member "improved algorithms for adaptive compressed sensing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "stronger l2 l2 compressed sensing without iterating")
  Member "on low risk heavy hitters and sparse recovery schemes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "improved algorithms for adaptive compressed sensing")
  Member "predicting positive and negative links with noisy queries theory practice":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "correlation clustering with adaptive similarity queries")
  Member "structured signal recovery from quadratic measurements breaking sample complexity barriers via nonconvex optimization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "toward a mathematical theory of the crystallographic phase retrieval problem")
  Member "almost optimal phaseless compressed sensing with sublinear decoding time":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "stronger l2 l2 compressed sensing without iterating")
  Member "sample efficient estimation and recovery in sparse fft via isolation on average":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "privacy preserving learning via deep net pruning")
  Member "stft phase retrieval uniqueness guarantees and recovery algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "toward a mathematical theory of the crystallographic phase retrieval problem")
  Member "sparse fourier transform in any constant dimension with nearly optimal sample complexity in sublinear time":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "nearly sample optimal sparse fourier transform in any dimension ripless and filterless")

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.DS(Data Structures and Algorithms)