human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "succinct representation of well spaced point clouds"
  Abstract: A set of n points in low dimensions takes Theta(n w) bits to store on a w-bit machine. Surface reconstruction and mesh refinement impose a requirement on the distribution of the points they process. I show how to use this assumption to lossily compress a set of n input points into a representation that takes only O(n) bits, independent of the word size. The loss can keep inter-point distances to within 10% relative error while still achieving a factor of three space savings. The representation allows standard quadtree operations, along with computing the restricted Voronoi cell of a point, in time O(w^2 + log n), which can be improved to time O(log n) if w is in Theta(log n). Thus one can use this compressed representation to perform mesh refinement or surface reconstruction in O(n) bits with only a logarithmic slowdown.

Connected through hyperedge HE-1 (induced by source paper "near optimal euclidean metric compression"):
  with members:
    - "optimality of the johnson lindenstrauss lemma"
    - "faster compressed quadtrees"

Connected through hyperedge HE-2 (induced by source paper "faster compressed quadtrees"):
  with members:
    - "layered label propagation a multiresolution coordinate free ordering for compressing social networks"
    - "fully functional static and dynamic succinct trees"

Question: Please tell me which class the center node 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)