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 "precise relaxation of the mumford shah functional"):
  Abstract: Jumps, edges and cutoffs are prevalent in our world across many modalities. The Mumford-Shah functional is a classical and elegant approach for modeling such discontinuities but global optimization of this non-convex functional remains challenging. The state of the art are convex representations based on the theory of calibrations. The major drawback of these approaches is the ultimate discretization of the co-domain into labels. For the case of total variation regularization, this issue has been partially resolved by recent sublabel-accurate relaxations, a generalization of which to other regularizers is not straightforward. In this work, we show that sublabel-accurate lifting approaches can be derived by discretizing a continuous relaxation of the Mumford-Shah functional by means of finite elements. We thereby unify and generalize existing functional lifting approaches. We show the efficiency of the proposed discretizations on discontinuity-preserving denoising tasks.

Includes members:
  Member "sublabel accurate convex relaxation of vectorial multilabel energies":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "lifting vectorial variational problems a natural formulation based on geometric measure theory and discrete exterior calculus")
  Member "submodular functions from discrete to continous domains":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "black box submodular maximization discrete and continuous settings")
  Member "sublabel accurate relaxation of nonconvex energies":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "ultrametric fitting by gradient descent")
  Member "continuous multiclass labeling approaches and algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "image labeling based on graphical models using wasserstein messages and geometric assignment")

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)