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 "higher order projected power iterations for scalable multi matching"):
  Abstract: The matching of multiple objects (e.g. shapes or images) is a fundamental problem in vision and graphics. In order to robustly handle ambiguities, noise and repetitive patterns in challenging real-world settings, it is essential to take geometric consistency between points into account. Computationally, the multi-matching problem is difficult. It can be phrased as simultaneously solving multiple (NP-hard) quadratic assignment problems (QAPs) that are coupled via cycle-consistency constraints. The main limitations of existing multi-matching methods are that they either ignore geometric consistency and thus have limited robustness, or they are restricted to small-scale problems due to their (relatively) high computational cost. We address these shortcomings by introducing a Higher-order Projected Power Iteration method, which is (i) efficient and scales to tens of thousands of points, (ii) straightforward to implement, (iii) able to incorporate geometric consistency, (iv) guarantees cycle-consistent multi-matchings, and (iv) comes with theoretical convergence guarantees. Experimentally we show that our approach is superior to existing methods.

Includes members:
  Member "product manifold filter non rigid shape correspondence via kernel density estimation in the product space":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mina convex mixed integer programming for non rigid shape alignment")
  Member "ds a flexible scalable and provably tight relaxation for matching problems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "mina convex mixed integer programming for non rigid shape alignment")
  Member "consistent multiple graph matching with multi layer random walks synchronization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "probabilistic permutation synchronization using the riemannian structure of the birkhoff polytope")
  Member "multi image semantic matching by mining consistent features":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "probabilistic permutation synchronization using the riemannian structure of the birkhoff polytope")
  Member "the projected power method an efficient algorithm for joint alignment from pairwise differences":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "optimal learning of joint alignments with a faulty oracle")
  Member "multi graph matching via affinity optimization with graduated consistency regularization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "adapnet adaptability decomposing encoder decoder network for weakly supervised action recognition and localization")
  Member "a flexible tensor block coordinate ascent scheme for hypergraph matching":
    also connected through other hyperedges:
      (none)
  Member "multi image matching via fast alternating minimization":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "crdoco pixel level domain transfer with cross domain consistency")

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)