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 "sampling based sublinear low rank matrix arithmetic framework for dequantizing quantum machine learning"):
  Abstract: We present an algorithmic framework generalizing quantum-inspired polylogarithmic-time algorithms on low-rank matrices. Our work follows the line of research started by Tang's breakthrough classical algorithm for recommendation systems [STOC'19]. The main result of this work is an algorithm for singular value transformation on low-rank inputs in the quantum-inspired regime, where singular value transformation is a framework proposed by Gilyen et al. [STOC'19] to study various quantum speedups. Since singular value transformation encompasses a vast range of matrix arithmetic, this result, combined with simple sampling lemmas from previous work, suffices to generalize all results dequantizing quantum machine learning algorithms to the authors' knowledge. Via simple black-box applications of our singular value transformation framework, we recover the dequantization results on recommendation systems, principal component analysis, supervised clustering, low-rank matrix inversion, low-rank semidefinite programming, and support vector machines. We also give additional dequantizations results on low-rank Hamiltonian simulation and discriminant analysis.

Includes members:
  Member "quantum inspired support vector machine":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a quantum inspired algorithm for general minimum conical hull problems")
  Member "a quantum inspired classical algorithm for recommendation systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "robust and sample optimal algorithms for psd low rank approximation")
  Member "a quantum inspired algorithm for general minimum conical hull problems":
    also connected through other hyperedges:
      (none)
  Member "quantum inspired classical sublinear time algorithm for solving low rank semidefinite programming via sampling approaches":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a quantum inspired algorithm for general minimum conical hull problems")
  Member "a quantum inspired classical algorithm for separable non negative matrix factorization":
    also connected through other hyperedges:
      (none)
  Member "quantum inspired low rank stochastic regression with logarithmic dependence on the dimension":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "robust and sample optimal algorithms for psd low rank approximation")
  Member "quantum inspired sublinear classical algorithms for solving low rank linear systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "robust and sample optimal algorithms for psd low rank approximation")
  Member "quantum inspired classical algorithms for principal component analysis and supervised clustering":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "quantum inspired classical sublinear time algorithm for solving low rank semidefinite programming via sampling approaches")

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)