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: "shapefit and shapekick for robust scalable structure from motion"
  Abstract: We introduce a new method for location recovery from pair-wise directions that leverages an efficient convex program that comes with exact recovery guarantees, even in the presence of adversarial outliers. When pairwise directions represent scaled relative positions between pairs of views (estimated for instance with epipolar geometry) our method can be used for location recovery, that is the determination of relative pose up to a single unknown scale. For this task, our method yields performance comparable to the state-of-the-art with an order of magnitude speed-up. Our proposed numerical framework is flexible in that it accommodates other approaches to location recovery and can be used to speed up other methods. These properties are demonstrated by extensively testing against state-of-the-art methods for location recovery on 13 large, irregular collections of images of real scenes in addition to simulated data with ground truth.

Connected through hyperedge HE-1 (induced by source paper "algebraic characterization of essential matrices and their averaging in multiview settings"):
  with members:
    - "resultant based incremental recovery of camera pose from pairwise matches"
    - "gpsfm global projective sfm using algebraic constraints on multi view fundamental matrices"
    - "rotation averaging and strong duality"
    - "a new rank constraint on multi view fundamental matrices and its application to camera location recovery"
    - "linear global translation estimation with feature tracks"
    - "robust camera location estimation by convex programming"

Connected through hyperedge HE-2 (induced by source paper "baseline desensitizing in translation averaging"):
  with members:
    - "a new rank constraint on multi view fundamental matrices and its application to camera location recovery"
    - "robust camera location estimation by convex programming"

Connected through hyperedge HE-3 (induced by source paper "robust rotation synchronization via low rank and sparse matrix decomposition"):
  with members:
    - "a survey of structure from motion"
    - "spectral synchronization of multiple views in se 3"
    - "on computing the translations norm in the epipolar graph"
    - "practical matrix completion and corruption recovery using proximal alternating robust subspace minimization"
    - "a solution for multi alignment by transformation synchronisation"
    - "cramer rao bounds for synchronization of rotations"
    - "robust camera location estimation by convex programming"
    - "low rank modeling and its applications in image analysis"

Connected through hyperedge HE-4 (induced by source paper "exact camera location recovery by least unsquared deviations"):
  with members:
    - "baseline desensitizing in translation averaging"
    - "estimation of camera locations in highly corrupted scenarios all about that base no shape trouble"
    - "a new rank constraint on multi view fundamental matrices and its application to camera location recovery"
    - "a survey of structure from motion"
    - "shapefit exact location recovery from corrupted pairwise directions"
    - "robust computation of linear models by convex relaxation"
    - "robust camera location estimation by convex programming"
    - "stable camera motion estimation using convex programming"

Connected through hyperedge HE-5 (induced by source paper "estimation of camera locations in highly corrupted scenarios all about that base no shape trouble"):
  with members:
    - "exact camera location recovery by least unsquared deviations"
    - "a new rank constraint on multi view fundamental matrices and its application to camera location recovery"
    - "a survey of structure from motion"
    - "shapefit exact location recovery from corrupted pairwise directions"
    - "robust camera location estimation by convex programming"
    - "stable camera motion estimation using convex programming"

Connected through hyperedge HE-6 (induced by source paper "gpsfm global projective sfm using algebraic constraints on multi view fundamental matrices"):
  with members:
    - "robust camera location estimation by convex programming"
    - "online algorithms for factorization based structure from motion"

Connected through hyperedge HE-7 (induced by source paper "adaptive relaxed admm convergence theory and practical implementation"):
  with members:
    - "tensor robust principal component analysis exact recovery of corrupted low rank tensors via convex optimization"
    - "non negative factorization of the occurrence tensor from financial contracts"
    - "adaptive admm with spectral penalty parameter selection"
    - "training neural networks without gradients a scalable admm approach"
    - "efficient training of very deep neural networks for supervised hashing"
    - "fast admm algorithm for distributed optimization with adaptive penalty"
    - "unwrapping admm efficient distributed computing via transpose reduction"
    - "robust camera location estimation by convex programming"

Connected through hyperedge HE-8 (induced by source paper "a survey of structure from motion"):
  with members:
    - "a survey on non filter based monocular visual slam systems"
    - "shapefit exact location recovery from corrupted pairwise directions"
    - "exact simultaneous recovery of locations and structure from known orientations and corrupted point correspondences"
    - "robust inference for visual inertial sensor fusion"
    - "robust camera location estimation by convex programming"
    - "stable camera motion estimation using convex programming"
    - "exact and stable recovery of rotations for robust synchronization"
    - "eigenvector synchronization graph rigidity and the molecule problem"

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.CV(Computer Vision and Pattern Recognition)