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 "fast and accurate tensor completion with tensor trains a system identification approach"):
  Abstract: We propose a novel tensor completion approach by equating it to a system identification task. The key is to regard the coordinates and values of the known entries as inputs and outputs, respectively. By assuming a tensor train format initialized with low-rank tensor cores, the latter are iteratively identified via a simple alternating linear scheme to reduce residuals. Experiments verify the superiority of the proposed scheme in terms of both speed and accuracy, where a speedup of up to 23$\times$ is observed compared to state-of-the-art tensor completion methods at a similar accuracy.

Includes members:
  Member "tensor robust principal component analysis exact recovery of corrupted low rank tensors via convex optimization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multi dimensional imaging data recovery via minimizing the partial sum of tubal nuclear norm")
  Member "efficient tensor completion for color image and video recovery low rank tensor train":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "low rank tensor grid for image completion")
  Member "tensor computation a new framework for high dimensional problems in eda":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "pasta a parallel sparse tensor algorithm benchmark suite")
  Member "efficient tensor completion low rank tensor train":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "wide compression tensor ring nets")
  Member "tensor network alternating linear scheme for mimo volterra system identification":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "deep compression of sum product networks on tensor networks")
  Member "parallel matrix factorization for low rank tensor completion":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "low rank tensor grid for image completion")
  Member "incoherence optimal matrix completion":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "matrix completion with prior subspace information via maximizing correlation")
  Member "bayesian cp factorization of incomplete tensors with automatic rank determination":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "low rank tensor grid for image completion")

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)