Calibrate 发表于 2025-3-26 22:04:27
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Linear SVM Models for Online Activity Recognitionithms differ on the norm of their formulation’s regularization term (whether it is the L1-, L2- or L1-L2-Norm). They allow to control over dimensionality reduction and classification accuracy while increasing the prediction speed when compared with kernelized SVM algorithms. Moreover, this chapter pAnthrp 发表于 2025-3-27 06:16:44
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Book 2015 exploiting the sensing, computing and communication capabilities currently available in these devices, the author developed a novel smartphone-based activity-recognition system, which takes into consideration all aspects of online human activity recognition, from experimental data collection, to ma精密 发表于 2025-3-27 14:35:34
se different data sources offers new opportunities, still largely underexploited, to improve the understanding, modeling, and reconstruction of geophysical dynamics. The classical way to reconstruct the space-time variations of a geophysical system from observations relies on data assimilation methoMortal 发表于 2025-3-27 17:59:58
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ductive approaches.Designed to help such readers understand ."Machine Learning and Data Mining for Computer Security" provides an overview of the current state of research in machine learning and data mining as it applies to problems in computer security. This book has a strong focus on information