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楼主: DART
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On Promise Problems: A Survey,urvey some of the applications that this notion has found in the twenty years that elapsed. These include the notion of “unique solutions”, the formulation of “gap problems” as capturing various approximation tasks, the identification of complete problems (especially for the class .), the indication
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https://doi.org/10.1007/978-3-322-92097-3iques that are suitable for the cipher structure, we also perform a comparison between the performance of these different techniques. Our implementation provides a high degree of robustness against attacks from execution environments where the adversary has access to the software implementation such as in digital right management applications.
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Degrading Detection Performance of Wireless IDSs Through Poisoning Feature Selection,can influence machine learning, including filter and embedded feature selection algorithms using three benchmark network public datasets and a wireless sensor network dataset, i.e., KDD99, NSL-KDD, Kyoto 2006+ and WSN-DS. Our results manifest that gradient poisoning method causes a significant drop in the classification accuracy of IDSs about 20%.
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Anna Shashkova,Michel Verlainetively integrated into functional learning spaces. Technology incorporated into these training environments includes high-speed video, wearable sensors, instrumented surfaces, as well as model simulation, computer vision, and data visualization tools to create a “smart” training space. Information g
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gn and analysis..The book has a rich collection of exercises. Several of them illustrate how the theory developed in the book may be used in various applications. Solutions to many of the exercises are included in an appendix..978-1-4614-2670-7978-0-387-93839-4Series ISSN 1431-875X Series E-ISSN 2197-4136
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