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 "streaming ptas for binary ell_0 low rank approximation"):
  Abstract: We give a 3-pass, polylog-space streaming PTAS for the constrained binary $k$-means problem and a 4-pass, polylog-space streaming PTAS for the binary $\ell_0$-low rank approximation problem. The connection between the above two problems has recently been studied. We design a streaming PTAS for the former and use this connection to obtain streaming PTAS for the latter. This is the first constant pass, polylog-space streaming algorithm for either of the two problems.

Includes members:
  Member "streaming ptas for constrained k means":
    also connected through other hyperedges:
      (none)
  Member "approximation schemes for low rank binary matrix approximation problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on clustering incomplete data")
  Member "a unified framework for clustering constrained data without locality property":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fair clustering with multiple colors")
  Member "on the complexity of robust pca and l1 norm low rank matrix approximation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "low rank approximation from communication complexity")
  Member "generalized independent component analysis over finite alphabets":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on universal features for high dimensional learning and inference")
  Member "faster algorithms for the constrained k means problem":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fair clustering with multiple colors")
  Member "low rank approximation of binary matrices column subset selection and generalizations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "optimal analysis of subset selection based l_p low rank approximation")
  Member "a simple d 2 sampling based ptas for k means and other clustering problems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "simple and sharp analysis of k means")

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)