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Titlebook: Wie Unternehmen von Theater profitieren k?nnen; Führung spielend ler Hans Joachim Hoppe,Jürgen Jünger,Tilo Esche Book 2017 Springer Fachmed

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21#
發(fā)表于 2025-3-25 06:57:54 | 只看該作者
Georg Felserhldeckel und auch manchmal in den ., die hie und da so gelb aussehen, dafs man sie für geschwürig halten m?chte. Man findet die blafse Schleimhaut bei allen Kranken, die an mangelhafter Blutbildung leiden, an An?mie, an Chlorose, Anaemia perniciosa, Leukaemia, im Erholungsstadium nach schweren Erkra
22#
發(fā)表于 2025-3-25 08:11:17 | 只看該作者
23#
發(fā)表于 2025-3-25 12:50:33 | 只看該作者
Darwinian Evolution: Process or Pattern?can be measured by focusing on changes in DNA/allele frequencies. However, in some publications it has been suggested that selection represents a state, not a process. If this is true any definition of Darwinian evolution that includes selection no longer can represent a process, because the ontolog
24#
發(fā)表于 2025-3-25 18:00:34 | 只看該作者
Declarative Preferences in Reactive BDI Agentsirst-available plan. Priority between plans is hard-coded in the program, and so the reasons why a certain plan is preferred remain in the programmer’s mind. Recent works that attempt to include explicit preferences in BDI agents treat preferences essentially as a rationale for planning tasks to be
25#
發(fā)表于 2025-3-25 21:06:04 | 只看該作者
Noise Adaptive Tensor Train Decomposition for Low-Rank Embedding of Noisy Dataself is expensive and subject to dimensionality curse. Tensor train decomposition is designed to avoid the explosion of intermediary data, which plagues other tensor decomposition techniques. However, many tensor decomposition schemes, including tensor train decomposition is sensitive to noise in th
26#
發(fā)表于 2025-3-26 00:51:26 | 只看該作者
27#
發(fā)表于 2025-3-26 06:08:59 | 只看該作者
28#
發(fā)表于 2025-3-26 10:33:35 | 只看該作者
29#
發(fā)表于 2025-3-26 15:23:41 | 只看該作者
30#
發(fā)表于 2025-3-26 17:14:38 | 只看該作者
Gesine D?rr,Michael Marx,Reimund Prokein,Wolfram Oettler,Raik Severin,Robert Nechwatal,Karin Mengng on the output language, we can divide all approaches to automatic knowledge acquisition into two categories: symbolic and non-symbolic. Non-symbolic systems do not represent knowledge explicitly. For example, in statistical models knowledge is represented as a set of examples together with some s
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