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 "making laplacians commute"):
  Abstract: In this paper, we construct multimodal spectral geometry by finding a pair of closest commuting operators (CCO) to a given pair of Laplacians. The CCOs are jointly diagonalizable and hence have the same eigenbasis. Our construction naturally extends classical data analysis tools based on spectral geometry, such as diffusion maps and spectral clustering. We provide several synthetic and real examples of applications in dimensionality reduction, shape analysis, and clustering, demonstrating that our method better captures the inherent structure of multi-modal data.

Includes members:
  Member "almost commuting matrices are almost jointly diagonalizable":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "asymptotic metrics on the space of matrices under the commutation relation")
  Member "clustering on multi layer graphs via subspace analysis on grassmann manifolds":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "learning graphs from data a signal representation perspective")
  Member "coupled quasi harmonic bases":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "operatornet recovering 3d shapes from difference operators")
  Member "multimodal diffusion geometry by joint diagonalization of laplacians":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi modal image retrieval with random walk on multi layer graphs")
  Member "sparse modeling of intrinsic correspondences":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "graph domain adaptation with localized graph signal representations")
  Member "learning multi modal similarity":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a similarity measure for material appearance")

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)