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 "matrix recipes for hard thresholding methods"):
  Abstract: In this paper, we present and analyze a new set of low-rank recovery algorithms for linear inverse problems within the class of hard thresholding methods. We provide strategies on how to set up these algorithms via basic ingredients for different configurations to achieve complexity vs. accuracy tradeoffs. Moreover, we study acceleration schemes via memory-based techniques and randomized, $\epsilon$-approximate matrix projections to decrease the computational costs in the recovery process. For most of the configurations, we present theoretical analysis that guarantees convergence under mild problem conditions. Simulation results demonstrate notable performance improvements as compared to state-of-the-art algorithms both in terms of reconstruction accuracy and computational complexity.

Includes members:
  Member "solving quadratic equations via phaselift when there are about as many equations as unknowns":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "phase retrieval of low rank matrices by anchored regression")
  Member "combinatorial selection and least absolute shrinkage via the clash algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "quantitative recovery conditions for tree based compressed sensing")
  Member "matrix alps accelerated low rank and sparse matrix reconstruction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "low rank approximation from communication complexity")
  Member "online robust subspace tracking from partial information":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deep autoencoders with value at risk thresholding for unsupervised anomaly detection")
  Member "online identification and tracking of subspaces from highly incomplete information":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "online high rank matrix completion")
  Member "guaranteed rank minimization via singular value projection":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the importance of phase in complex compressive sensing")
  Member "matrix completion from a few entries":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "matrix completion with prior subspace information via maximizing correlation")
  Member "robust principal component analysis":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "finding the sparsest vectors in a subspace theory algorithms and applications")

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.NA(Numerical Analysis)