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Titlebook: Von der Kollegialit?t zur Hierarchie?; Eine Analyse des New Otto Hüther Book 2010 VS Verlag für Sozialwissenschaften | Springer Fachmedien

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發(fā)表于 2025-3-23 09:44:43 | 只看該作者
12#
發(fā)表于 2025-3-23 17:06:59 | 只看該作者
Otto Hüther solutions are then handled by optimization techniques, in particular multi-objective, multiple choice Knapsack to determine the optimal cybersecurity investment. Our methodology provides security effective and cost efficient solutions especially against .. We believe our work can be used to advise
13#
發(fā)表于 2025-3-23 21:32:52 | 只看該作者
Otto Hütherrovide the following main contributions. We introduce a new meta-gradient based poisoning attack for various types of predict and optimize frameworks. We compare to a technique shown effective in computer vision. We find that the complexity of the problem makes attacking decision focused model diffi
14#
發(fā)表于 2025-3-23 22:50:08 | 只看該作者
between sub-games. Due to the large sizes of the action and state spaces, we present a technique that uses deep neural networks in conjunction with Q-learning to derive near-optimal Nash strategies for both attacker and defender. We assess the effectiveness of these policies by comparing them to opt
15#
發(fā)表于 2025-3-24 05:27:13 | 只看該作者
Otto Hütheration is NP-hard even in the zero-sum case. We provide an MILP formulation for the general problem with constraints on cost and feasibility, along with a pseudo-polynomial time algorithm for the special . setting. Second, for risk-averse attackers, we present a solution based on Prospect theoretic m
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發(fā)表于 2025-3-24 07:40:27 | 只看該作者
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發(fā)表于 2025-3-24 10:55:03 | 只看該作者
18#
發(fā)表于 2025-3-24 15:35:04 | 只看該作者
Otto Hütherm has the same structure as that of aggregating the preference orders of a single person with regard to several aspects of alternatives into a single preference order on the set of alternatives. For this reason, the theory of social choice comes logically not under the topic of collective action (as
19#
發(fā)表于 2025-3-24 19:28:33 | 只看該作者
20#
發(fā)表于 2025-3-25 02:45:37 | 只看該作者
Otto Hütherd stochastic game. To solve the game we follow an approach where attack and defense strategies co-evolve through reinforcement learning and self-play toward an equilibrium. Solutions proposed in previous work prove the feasibility of this approach for small infrastructures but do not scale to realis
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