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 "convex class model on symmetric positive definite manifolds"):
  Abstract: The effectiveness of Symmetric Positive Definite (SPD) manifold features has been proven in various computer vision tasks. However, due to the non-Euclidean geometry of these features, existing Euclidean machineries cannot be directly used. In this paper, we tackle the classification tasks with limited training data on SPD manifolds. Our proposed framework, named Manifold Convex Class Model, represents each class on SPD manifolds using a convex model and classification can be performed by computing distances to the convex models. We provide three methods based on different metrics to address the optimization problem of the smallest distance of a point to the convex model on SPD manifold. The efficacy of our proposed framework is demonstrated both on synthetic data and several computer vision tasks including object recognition, texture classification, person re-identification and traffic scene classification.

Includes members:
  Member "kernel sparse subspace clustering on symmetric positive definite manifolds":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multi level representation learning for deep subspace clustering")
  Member "geometry aware similarity learning on spd manifolds for visual recognition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a neural network based on spd manifold learning for skeleton based hand gesture recognition")
  Member "matching image sets via adaptive multi convex hull":
    also connected through other hyperedges:
      (none)
  Member "kernel methods on the riemannian manifold of symmetric positive definite matrices":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "identity preserving face recovery from stylized portraits")
  Member "geodesic exponential kernels when curvature and linearity conflict":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "bayesian optimization meets riemannian manifolds in robot learning")
  Member "extrinsic methods for coding and dictionary learning on grassmann manifolds":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "generalized visual information analysis via tensorial algebra")
  Member "sparse coding and dictionary learning for symmetric positive definite matrices a kernel approach":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sparse coding of shape trajectories for facial expression and action recognition")
  Member "compressive acquisition of dynamic scenes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "privacy preserving action recognition using coded aperture videos")

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.CV(Computer Vision and Pattern Recognition)