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: "computing the gromov hyperbolicity of a discrete metric space"
  Abstract: We give exact and approximation algorithms for computing the Gromov hyperbolicity of an n-point discrete metric space. We observe that computing the Gromov hyperbolicity from a fixed base-point reduces to a (max,min) matrix product. Hence, using the (max,min) matrix product algorithm by Duan and Pettie, the fixed base-point hyperbolicity can be determined in O(n^2.69) time. It follows that the Gromov hyperbolicity can be computed in O(n^3.69) time, and a 2-approximation can be found in O(n^2.69) time. We also give a (2 log_2 n)-approximation algorithm that runs in O(n^2) time, based on a tree-metric embedding by Gromov. We also show that hyperbolicity at a fixed base-point cannot be computed in O(n^2.05) time, unless there exists a faster algorithm for (max,min) matrix multiplication than currently known.

Connected through hyperedge HE-1 (induced by source paper "computationally tractable riemannian manifolds for graph embeddings"):
  with members:
    - "riemannian adaptive optimization methods"
    - "learning continuous hierarchies in the lorentz model of hyperbolic geometry"
    - "grassmannian learning embedding geometry awareness in shallow and deep learning"
    - "hyperbolic entailment cones for learning hierarchical embeddings"
    - "poincar e embeddings for learning hierarchical representations"
    - "node2vec scalable feature learning for networks"
    - "convolutional neural networks on graphs with fast localized spectral filtering"
    - "complex embeddings for simple link prediction"

Connected through hyperedge HE-2 (induced by source paper "eccentricity terrain of delta hyperbolic graphs"):
  with members:
    - "fast approximation and exact computation of negative curvature parameters of graphs"
    - "revisiting radius diameter and all eccentricity computation in graphs through certificates"
    - "core congestion is inherent in hyperbolic networks"
    - "metric tree like structures in real life networks an empirical study"

Connected through hyperedge HE-3 (induced by source paper "fast approximation and exact computation of negative curvature parameters of graphs"):
  with members:
    - "effect of gromov hyperbolicity parameter on cuts and expansions in graphs and some algorithmic implications"
    - "fully polynomial fpt algorithms for some classes of bounded clique width graphs"
    - "when can graph hyperbolicity be computed in linear time"
    - "core congestion is inherent in hyperbolic networks"
    - "an improved combinatorial algorithm for boolean matrix multiplication"
    - "into the square on the complexity of quadratic time solvable problems"

Connected through hyperedge HE-4 (induced by source paper "hyperbolic intersection graphs and quasi polynomial time"):
  with members:
    - "solving vertex cover in polynomial time on hyperbolic random graphs"
    - "a framework for eth tight algorithms and lower bounds in geometric intersection graphs"
    - "finding hitting and packing cycles in subexponential time on unit disk graphs"
    - "the limited blessing of low dimensionality when 1 1 d is the best possible exponent for d dimensional geometric problems"
    - "subexponential parameterized algorithms for graphs of polynomial growth"
    - "on the diameter of hyperbolic random graphs"
    - "complexity dichotomy on partial grid recognition"

Connected through hyperedge HE-5 (induced by source paper "why did the shape of your network change on detecting network anomalies via non local curvatures"):
  with members:
    - "fast approximation and exact computation of negative curvature parameters of graphs"
    - "effect of gromov hyperbolicity parameter on cuts and expansions in graphs and some algorithmic implications"
    - "forman ricci flow for change detection in large dynamic data sets"
    - "euclidean versus hyperbolic congestion in idealized versus experimental networks"

Connected through hyperedge HE-6 (induced by source paper "effect of gromov hyperbolicity parameter on cuts and expansions in graphs and some algorithmic implications"):
  with members:
    - "the complexity of approximating vertex expansion"
    - "euclidean versus hyperbolic congestion in idealized versus experimental networks"
    - "reductions between expansion problems"

Connected through hyperedge HE-7 (induced by source paper "fully polynomial fpt algorithms for some classes of bounded clique width graphs"):
  with members:
    - "the use of a pruned modular decomposition for maximum matching algorithms on some graph classes"
    - "efficient and adaptive parameterized algorithms on modular decompositions"
    - "parameterized aspects of triangle enumeration"
    - "on the power of tree depth for fully polynomial fpt algorithms"
    - "when can graph hyperbolicity be computed in linear time"
    - "the power of data reduction for matching"
    - "tight hardness results for distance and centrality problems in constant degree graphs"
    - "fully polynomial time parameterized computations for graphs and matrices of low treewidth"

Connected through hyperedge HE-8 (induced by source paper "when can graph hyperbolicity be computed in linear time"):
  with members:
    - "towards improving brandes algorithm for betweenness centrality"
    - "fully polynomial fpt algorithms for some classes of bounded clique width graphs"
    - "polynomial fixed parameter algorithms a case study for longest path on interval graphs"

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)