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 "on clustering incomplete data"):
  Abstract: We study fundamental clustering problems for incomplete data. In this setting, we are given a set of incomplete d-dimensional Boolean vectors (representing the rows of a matrix), and the goal is to complete the missing vector entries so that the set of complete vectors admits a partitioning into at most k clusters with radius or diameter at most r. We develop a toolkit and use it to give tight characterizations of the parameterized complexity of these problems with respect to the parameters k, r, and the minimum number of rows and columns needed to cover all the missing entries. We show that the aforementioned problems are fixed-parameter tractable when parameterized by the three parameters combined, and that dropping any of these three parameters results in parameterized intractability. We extend this toolkit to settle the parameterized complexity of other clustering problems, answering an open question along the way. We also show how our results can be extended to data over any constant-size domain. A byproduct of our results is that, for the complete data setting, all problems under consideration are fixed-parameter tractable parameterized by k+r.

Includes members:
  Member "parameterized k clustering the distance matters":
    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 "low rank binary matrix approximation in column sum norm")
  Member "parameterized algorithms for the matrix completion problem":
    also connected through other hyperedges:
      (none)
  Member "approximation algorithms for stochastic clustering":
    also connected through other hyperedges:
      (none)
  Member "parameterized low rank binary matrix approximation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "low rank approximation from communication complexity")
  Member "independence clustering without a matrix":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hypotheses testing on infinite random graphs")
  Member "dispersion on trees":
    also connected through other hyperedges:
      (none)
  Member "mapreduce and streaming algorithms for diversity maximization in metric spaces of bounded doubling dimension":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "coreset based strategies for robust center type problems")

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)