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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A Learning Algorithm for Piecewise Linear Regressionork so as to reconstruct a target function assuming a different linear behavior on each set of a polyhedral partition of the input domain..The proposed method combine local estimation, clustering in weight space, classification and regression in order to achieve the desired result. A simulation on a

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Note Relevance Determinationleaning of a model‘s structure. We call the prior . It is applicable in a range of models including sigmoid belief networks and Boltzmann machines. We demonstrate how the approach may be applied to determine structure in a multi-layer perceptron.

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Learning Distributed Representations of Relational Data using Linear Relational Embeddingn concepts. The final goal of LRE is to be able to generalize, i.e. to infer new relations among the concepts. The version presented here is capable of handling incomplete information and multiple correct answers. We present results on two simple domains, that show an excellent generalization perfor

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Payoff-monotonic Game Dynamics for the Maximum Clique Problemuccess to combinatorial optimization problems such as the maximum clique problem. This paper substantially expands on previous work along these lines, by proposing . dynamics, a wide family of game dynamics of which replicator equations are just a special instance. Experiments show that this class c

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1431-6854 -Ol, jointly organized by the International Institute for Advanced 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 scientist

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Solving Min Vertex Cover with Iterated Hopfield Networks sequence length and experimentally compare on random graphs the performances (quality of solutions, computation time) of the algorithm with those of other known heuristics. The experiments show that the quality of the solutions found by the neural algorithm is quite satisfactory.

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