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: "on affine rigidity"
  Abstract: We define the notion of affine rigidity of a hypergraph and prove a variety of fundamental results for this notion. First, we show that affine rigidity can be determined by the rank of a specific matrix which implies that affine rigidity is a generic property of the hypergraph.Then we prove that if a graph is is $(d+1)$-vertex-connected, then it must be "generically neighborhood affinely rigid" in $d$-dimensional space. This implies that if a graph is $(d+1)$-vertex-connected then any generic framework of its squared graph must be universally rigid. #R##N#Our results, and affine rigidity more generally, have natural applications in point registration and localization, as well as connections to manifold learning.

Connected through hyperedge HE-1 (induced by source paper "a unified dissertation on bearing rigidity theory"):
  with members:
    - "bearing rigidity theory and its applications for control and estimation of network systems life beyond distance rigidity"
    - "quantization effects and convergence properties of rigid formation control systems with quantized distance measurements"
    - "laman graphs are generically bearing rigid in arbitrary dimensions"
    - "bearing rigidity and almost global bearing only formation stabilization"
    - "decentralized rigidity maintenance control with range measurements for multi robot systems"

Connected through hyperedge HE-2 (induced by source paper "on uniquely registrable networks"):
  with members:
    - "large scale sensor network localization via rigid subnetwork registration"
    - "distributed maximum likelihood sensor network localization"
    - "global registration of multiple point clouds using semidefinite programming"
    - "eigenvector synchronization graph rigidity and the molecule problem"

Connected through hyperedge HE-3 (induced by source paper "combinatorial rigidity of incidence systems and application to dictionary learning"):
  with members:
    - "optimal decomposition and recombination of isostatic geometric constraint systems for designing layered materials"
    - "reduction of constraint systems"
    - "new algorithms for learning incoherent and overcomplete dictionaries"
    - "learning sparsely used overcomplete dictionaries via alternating minimization"
    - "the algebraic combinatorial approach for low rank matrix completion"
    - "generalized principal component analysis gpca"
    - "exact recovery of sparsely used dictionaries"
    - "combinatorics and the rigidity of cad systems"

Connected through hyperedge HE-4 (induced by source paper "an incidence geometry approach to dictionary learning"):
  with members:
    - "new algorithms for learning incoherent and overcomplete dictionaries"
    - "learning sparsely used overcomplete dictionaries via alternating minimization"
    - "generalized principal component analysis gpca"
    - "exact recovery of sparsely used dictionaries"
    - "combinatorics and the rigidity of cad systems"
    - "body and cad geometric constraint systems"

Connected through hyperedge HE-5 (induced by source paper "global registration of multiple point clouds using semidefinite programming"):
  with members:
    - "robust computation of linear models by convex relaxation"
    - "manopt a matlab toolbox for optimization on manifolds"
    - "approximating the little grothendieck problem over the orthogonal and unitary groups"
    - "incremental computation of pseudo inverse of laplacian theory and applications"
    - "exact and stable recovery of rotations for robust synchronization"
    - "efficient rounding for the noncommutative grothendieck inequality"
    - "eigenvector synchronization graph rigidity and the molecule problem"
    - "phaselift exact and stable signal recovery from magnitude measurements via convex programming"

Connected through hyperedge HE-6 (induced by source paper "stable camera motion estimation using convex programming"):
  with members:
    - "robust computation of linear models by convex relaxation"
    - "robust camera location estimation by convex programming"
    - "global registration of multiple point clouds using semidefinite programming"
    - "exact and stable recovery of rotations for robust synchronization"
    - "phaselift exact and stable signal recovery from magnitude measurements via convex programming"
    - "robust pca via outlier pursuit"
    - "robust principal component analysis"
    - "exact matrix completion via convex optimization"

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)