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 "stabilizing the output of persistent homology computations"):
  Abstract: We propose a general technique for extracting a larger set of stable information from persistent homology computations than is currently done. The persistent homology algorithm is generally seen as a procedure which starts with a filtered complex and ends with a persistence diagram. This procedure is stable (at least to certain types of pertur- bations of the input), and so using the diagram as a signature of the input - for example, deriving features from it that are then used in machine learning - is a well-justified con- cept. However, these computations also produce a great deal of other potentially useful but unstable information: for example, each point in the diagram corresponds to a specific positive simplex. In addition, the persistence diagram is not stable with respect to other procedures that are employed in practice, such as thresholding a point cloud by density. We recast these problems as real-valued functions which are discontinuous but measur- able, and then observe that convolving such a function with a Lipschitz function produces a Lipschitz function. The resulting stable function is easily estimated. We illustrate this approach with numerous examples and several experiments.

Includes members:
  Member "topological and statistical behavior classifiers for tracking applications":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "stabilizing the unstable output of persistent homology computations")
  Member "graph induced complex on point data":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "topological data analysis with epsilon net induced lazy witness complex")

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.CG(Computational Geometry)