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 "continuous relaxation of map inference a nonconvex perspective"):
  Abstract: In this paper, we study a nonconvex continuous relaxation of MAP inference in discrete Markov random fields (MRFs). We show that for arbitrary MRFs, this relaxation is tight, and a discrete stationary point of it can be easily reached by a simple block coordinate descent algorithm. In addition, we study the resolution of this relaxation using popular gradient methods, and further propose a more effective solution using a multilinear decomposition framework based on the alternating direction method of multipliers (ADMM). Experiments on many real-world problems demonstrate that the proposed ADMM significantly outperforms other nonconvex relaxation based methods, and compares favorably with state of the art MRF optimization algorithms in different settings.

Includes members:
  Member "alternating direction graph matching":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mina convex mixed integer programming for non rigid shape alignment")
  Member "a new look at reweighted message passing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "map inference via block coordinate frank wolfe algorithm")
  Member "a comparative study of modern inference techniques for structured discrete energy minimization problems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "worst case polynomial time exact map inference on discrete models with global dependencies")
  Member "efficient mrf energy minimization via adaptive diminishing smoothing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "map inference via l2 sphere linear program reformulation")
  Member "opengm a c library for discrete graphical models":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "referring expression grounding by marginalizing scene graph likelihood")
  Member "efficiently searching for frustrated cycles in map inference":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "graph structured prediction energy networks")

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)