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Titlebook: Meta-Learning in Computational Intelligence; Norbert Jankowski,W?odzis?aw Duch,Krzysztof Gra?bc Book 2011 Springer Berlin Heidelberg 2011

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樓主: HAG
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發(fā)表于 2025-3-25 04:13:14 | 只看該作者
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發(fā)表于 2025-3-25 09:32:08 | 只看該作者
Optimal Support Features for Meta-Learning,this area involved heterogeneous learning systems combined with a complexity-guided search for optimal models, performed within the framework of (dis)similarity based methods to discover “knowledge granules”. This approach, inspired by neurocognitive mechanisms of information processing in the brain
23#
發(fā)表于 2025-3-25 15:17:09 | 只看該作者
phase diagram is not sufficient to describe the state of the system during its time-evolution, and its possible approach to the steady state. For this reason, we also discuss the nonequilibrium dynamics resulting from the interplay between losses and external driving in some relevant cases.
24#
發(fā)表于 2025-3-25 19:54:12 | 只看該作者
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發(fā)表于 2025-3-25 23:01:45 | 只看該作者
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發(fā)表于 2025-3-26 02:28:54 | 只看該作者
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發(fā)表于 2025-3-26 05:10:13 | 只看該作者
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發(fā)表于 2025-3-26 11:55:54 | 只看該作者
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發(fā)表于 2025-3-26 15:06:51 | 只看該作者
30#
發(fā)表于 2025-3-26 18:58:00 | 只看該作者
Ricardo B. C. Prudêncio,Marcilio C. P. de Souto,Teresa B. Ludermir non-relativistic matter field, i.e., the Schr?dinger field, which offers a powerful tool for theinvestigation of many-body problems, and of atomic quantum optics and entanglement. Finally, two new chapters introduce the finite-temperature functional integration of bosonic and fermionic fields for t
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