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Titlebook: Artificial Neural Networks - ICANN 2008; 18th International C Véra K?rková,Roman Neruda,Jan Koutník Conference proceedings 2008 Springer-Ve

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41#
發(fā)表于 2025-3-28 14:45:01 | 只看該作者
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https://doi.org/10.1007/978-3-642-66276-8exploiting binary supervision. The model guarantees to compute a non negative and symmetric measure, and shows good generalization capabilities even if a small set of supervised examples is used for training. The approximation capabilities of the proposed model are also investigated. Moreover, the e
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發(fā)表于 2025-3-30 03:56:31 | 只看該作者
Fennoscandian Tundra Ecosystemsexperts in professional games. The ability to predict experts’ moves is useful, because it can, in principle, be used to narrow the search done by a computer Go player. We applied an ensemble of convolutional neural networks to this problem. Our main result is that the ensemble learns to predict 36.
50#
發(fā)表于 2025-3-30 04:09:28 | 只看該作者
https://doi.org/10.1007/978-3-642-80937-8eral associative models have been proposed by different authors. However, they have several constraints which limit their applicability in complex pattern recognition problems. In this paper we gather different results provided by a dynamic associative model and present new results in order to descr
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