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 "tree based iterated local search for markov random fields with applications in image analysis"):
  Abstract: The \emph{maximum a posteriori} (MAP) assignment for general structure Markov random fields (MRFs) is computationally intractable. In this paper, we exploit tree-based methods to efficiently address this problem. Our novel method, named Tree-based Iterated Local Search (T-ILS) takes advantage of the tractability of tree-structures embedded within MRFs to derive strong local search in an ILS framework. The method efficiently explores exponentially large neighborhood and does so with limited memory without any requirement on the cost functions. We evaluate the T-ILS in a simulation of Ising model and two real-world problems in computer vision: stereo matching, image denoising. Experimental results demonstrate that our methods are competitive against state-of-the-art rivals with a significant computational gain.

Includes members:
  Member "a comparative study of modern inference techniques for structured discrete energy minimization problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "worst case polynomial time exact map inference on discrete models with global dependencies")
  Member "loopy belief propagation for approximate inference an empirical study":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "analyzing differentiable fuzzy logic operators")
  Member "convergent message passing algorithms a unifying view":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "graph structured prediction energy networks")
  Member "map estimation of semi metric mrfs via hierarchical graph cuts":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "accelerated inference in markov random fields via smooth riemannian optimization")
  Member "on the optimality of tree reweighted max product message passing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "partial optimality of dual decomposition for map inference in pairwise mrfs")
  Member "norm product belief propagation primal dual message passing for approximate inference":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "scalable explanation of inferences on large graphs")
  Member "equivalence of lp relaxation and max product for weighted matching in general graphs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "message passing and combinatorial optimization")
  Member "lagrangian relaxation for map estimation in graphical models":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "map inference via l2 sphere linear program reformulation")

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.AI(Artificial Intelligence)