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Titlebook: Second Generation Expert Systems; Jean-Marc David,Jean-Paul Krivine,Reid Simmons Conference proceedings 1993 Springer-Verlag Berlin Heidel

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Phyllis A. Kotonludes a mixed key-based and tuple-based partitioning scheme to handle skewed data in each side of the bipartite graph-based model, a strategy for redistribution of query nodes in two sides of this model, and a migration algorithm about state consistency to support full-history joins. Experiments sho
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Walter Hamschererience to perception. Some c-granules are extended by information layers, called informational c-granules (ic-granules, for short); they can create the basis for modeling a notion of . conducting the whole process of computation over the c-granules.
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Tom Bylander,Michael Weintraub,Sheldon R. Simon membership functions from sampling distributions, 4) feature classifications with maximum mutual information criterion, 5) proving the convergence of the expectation-maximization algorithm for mixture models, 6) interpreting Popper’s verisimilitude and reconciling the contradiction between the cont
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John E. Hunt,Christopher J. Price membership functions from sampling distributions, 4) feature classifications with maximum mutual information criterion, 5) proving the convergence of the expectation-maximization algorithm for mixture models, 6) interpreting Popper’s verisimilitude and reconciling the contradiction between the cont
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Walter Van de Velde. Then, it improves them by the directed search method. DSMOA-KCS is compared with several existing state-of-the-art algorithms (NSGA-III, RSEA, and MOEADPas) on many-objective problems with 5 to 30 objective functions using the Inverted Generational Distance (IGD) performance metric. DSMOA-KCS eval
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