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 "mina convex mixed integer programming for non rigid shape alignment"):
  Abstract: We present a convex mixed-integer programming formulation for non-rigid shape matching. To this end, we propose a novel shape deformation model based on an efficient low-dimensional discrete model, so that finding a globally optimal solution is tractable in (most) practical cases. Our approach combines several favourable properties: it is independent of the initialisation, it is much more efficient to solve to global optimality compared to analogous quadratic assignment problem formulations, and it is highly flexible in terms of the variants of matching problems it can handle. Experimentally we demonstrate that our approach outperforms existing methods for sparse shape matching, that it can be used for initialising dense shape matching methods, and we showcase its flexibility on several examples.

Includes members:
  Member "zoomout spectral upsampling for efficient shape correspondence":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deep geometric matrix completion are we doing it right")
  Member "continuous and orientation preserving correspondences via functional maps":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "unsupervised cycle consistent deformation for shape matching")
  Member "unsupervised deep learning for structured shape matching":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "instant recovery of shape from spectrum via latent space connections")
  Member "deep functional maps structured prediction for dense shape correspondence":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deep graph matching consensus")
  Member "product manifold filter non rigid shape correspondence via kernel density estimation in the product space":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "harmonic alignment")
  Member "ds a flexible scalable and provably tight relaxation for matching problems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "wasserstein based graph alignment")
  Member "a combinatorial solution to non rigid 3d shape to image matching":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "3dregnet a deep neural network for 3d point registration")
  Member "efficient globally optimal 2d to 3d deformable shape matching":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "pix3d dataset and methods for single image 3d shape modeling")

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)