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 "and or multi valued decision diagrams aomdds for graphical models"):
  Abstract: Inspired by the recently introduced framework of AND/OR search spaces for graphical models, we propose to augment Multi-Valued Decision Diagrams (MDD) with AND nodes, in order to capture function decomposition structure and to extend these compiled data structures to general weighted graphical models (e.g., probabilistic models). We present the AND/OR Multi-Valued Decision Diagram (AOMDD) which compiles a graphical model into a canonical form that supports polynomial (e.g., solution counting, belief updating) or constant time (e.g. equivalence of graphical models) queries. We provide two algorithms for compiling the AOMDD of a graphical model. The first is search-based, and works by applying reduction rules to the trace of the memory intensive AND/OR search algorithm. The second is inference-based and uses a Bucket Elimination schedule to combine the AOMDDs of the input functions via the the APPLY operator. For both algorithms, the compilation time and the size of the AOMDD are, in the worst case, exponential in the treewidth of the graphical model, rather than pathwidth as is known for ordered binary decision diagrams (OBDDs). We introduce the concept of semantic treewidth, which helps explain why the size of a decision diagram is often much smaller than the worst case bound. We provide an experimental evaluation that demonstrates the potential of AOMDDs.

Includes members:
  Member "value elimination bayesian inference via backtracking search":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the sum product theorem a foundation for learning tractable models")
  Member "new advances in inference by recursive conditioning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "case factor diagrams for structured probabilistic modeling")
  Member "case factor diagrams for structured probabilistic modeling":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an algebraic formalization of forward and forward backward algorithms")
  Member "mixtures of deterministic probabilistic networks and their and or search space":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "world knowledge as indirect supervision for document clustering")
  Member "the relationship between and or search and variable elimination":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the sum product theorem a foundation for learning tractable models")
  Member "and or multi valued decision diagrams aomdds for weighted graphical models":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "solving sat and bayesian inference with backtracking search")
  Member "a knowledge compilation map":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "abstracting probabilistic models a logical perspective")

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)