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Titlebook: Artificial Neural Networks and Machine Learning -- ICANN 2012; 22nd International C Alessandro E. P. Villa,Włodzisław Duch,Günther Pal Conf

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/162633.jpg
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Effective Actions and Anomaliesihood Hebbian Learning (MLHL) network designed for modern many-core graphics processing units (GPUs). The parallel implementation as well as the computational experiments conducted in order to evaluate the speedup achieved by the GPU are presented and discussed. The evaluation was done on a well-known artificial data set, the 2D bars data set.
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Flavor chemistry and assessment,ts search space is full of crevasse-like forms having huge condition numbers; thus, it is very hard for existing methods to perform efficient search in such a space. The space also includes the structure of reducibility mapping. The paper proposes a new search method for a complex-valued MLP, which
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Flavour chemistry of fermented sausages,dth, are investigated in the framework of scaled kernels. The impact of widths of kernels on approximation of multivariable functions, generalization modelled by regularization with kernel stabilizers, and minimization of error functionals is analyzed.
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Historical aspects of meat fermentations,els, but rather the permutation of that set that applies to a new example (e.g., the ranking of a set of financial analysts in terms of the quality of their recommendations). In this paper, we adapt a multilayer perceptron algorithm for label ranking. We focus on the adaptation of the Back-Propagati
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