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 "a quantum computational approach to correspondence problems on point sets"):
  Abstract: Modern adiabatic quantum computers (AQC) are already used to solve difficult combinatorial optimisation problems in various domains of science. Currently, only a few applications of AQC in computer vision have been demonstrated. We review modern AQC and derive the first algorithm for transformation estimation and point set alignment suitable for AQC. Our algorithm has a subquadratic computational complexity of state preparation. We perform a systematic experimental analysis of the proposed approach and show several examples of successful point set alignment by simulated sampling. With this paper, we hope to boost the research on AQC for computer vision.

Includes members:
  Member "quantum algorithm implementations for beginners":
    also connected through other hyperedges:
      (none)
  Member "nonnegative binary matrix factorization with a d wave quantum annealer":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "support vector machines on the d wave quantum annealer")
  Member "fast clique minor generation in chimera qubit connectivity graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "performance of a quantum annealer for ising ground state computations on chimera graphs")
  Member "point set registration coherent point drift":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "3d point cloud processing and learning for autonomous driving")

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)