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Titlebook: Machtfaktor auch ohne Machtbasis?; Die Sudetendeutsche Gerhard Hopp Book 2010 VS Verlag für Sozialwissenschaften | Springer Fachmedien Wie

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41#
發(fā)表于 2025-3-28 16:34:03 | 只看該作者
,Resumée und theoretische Schlussfolgerungen,zwerken zwischen Parteien und Verb?nden trotz abnehmender Bedeutung der vom Verband vertretenen sozialen Gruppe, zurückgespannt und damit der Kreis der vorliegenden Studie geschlossen werden. So werden zum einen die These, Hypothesen sowie das Variablenset, welche in der Theoriesynthese erarbeitet w
42#
發(fā)表于 2025-3-28 21:43:19 | 只看該作者
in machine learning models and to improve the models in the Machine learning algorithms allow computers to learn without being explicitly programmed. Their application is now spreading to highly sophisticated tasks across multiple domains, such as medical diagnostics or fully autonomous vehicles. Wh
43#
發(fā)表于 2025-3-29 02:39:20 | 只看該作者
44#
發(fā)表于 2025-3-29 05:45:29 | 只看該作者
Gerhard HoppDRL). These techniques are to work with individual safety properties, such as the robustness of a data instance . (for CNN) or the safety of a policy . on a given initial state .. (for DRL). However, considering that deep learning models usually serve as components of a large autonomous system, the
45#
發(fā)表于 2025-3-29 07:15:45 | 只看該作者
Gerhard Hoppe soundness and completeness required by the mathematical proof result in the scalability problem that verification algorithms can only work with either small models (e.g., the MILP-based method as in Sect. .) or limited number of input dimensions (e.g., the reachability analysis as in Sect. .). In
46#
發(fā)表于 2025-3-29 15:09:28 | 只看該作者
Gerhard Hoppluding perceptron and why we need multi-layer structures, how the convolutional neural networks extract features layer by layer, the back-propagation learning algorithm, and the functional layers of convolutional neural networks. Then, we will focus on the safety and security vulnerabilities of deep
47#
發(fā)表于 2025-3-29 16:19:21 | 只看該作者
48#
發(fā)表于 2025-3-29 22:57:55 | 只看該作者
Gerhard Hoppta and feedback from actual PFA analysis.Discusses practical.This book provides a state-of-the-art guide to Machine Learning (ML)-based techniques that have been shown to be highly efficient for diagnosis of failures in electronic circuits and systems. The methods discussed can be used for volume di
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