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Titlebook: Neural Nets WIRN Vietri-01; Proceedings of the 1 Roberto Tagliaferri (Associate Professor of Comput Conference proceedings 2002 Springer-Ve

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楼主: 尖酸好
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Detecting uncertainty regions for characterizing classification problems of optimal decision functions can be derived..A general method for detecting the uncertainty region in real-world problems is then proposed, whose implementation can vary according to the connectionist model employed. Its application allows to improve the performance of the resulting neural network.
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Support Vector Machines for uncertainty region detection the Generalized Optimal Hyperplane is shown to be effective..As in the Support Vector Machine approach, kernel functions can be used to generalize the proposed technique, so as to detect uncertainty regions with nonlinear boundaries. Simulations concerning artificial benchmarks show the quality of the resulting method.
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A Learning Algorithm for Piecewise Linear Regressiond method combine local estimation, clustering in weight space, classification and regression in order to achieve the desired result. A simulation on a benchmark problem shows the good properties of this new learning algorithm.
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Payoff-monotonic Game Dynamics for the Maximum Clique Problem by proposing . dynamics, a wide family of game dynamics of which replicator equations are just a special instance. Experiments show that this class contains dynamics which are considerably faster than and as accurate as replicator equations.
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Conference proceedings 2002Advanced Scientific Studies "Eduardo R. Caianiello" (IIASS), the Societa Italiana Reti Neuroniche (SIREN), the IEEE NNC Italian RIG and the Italian SIG of the INNS. Following the tradition of previous years, we invited three foreign scientists to the workshop, Dr. G. Indiveri and Professors A. Roy a
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Phase Transitions in a Neural Model of Problem Solvingspecific heat and . the temperature, as defined by Smolensky, in order to find evidence for phase transitions in a simulated learning process. We found only partial evidence of such phase transitions. Besides, the network performance was strongly dependent on the structuration of initial dotation of knowledge atoms.
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