Machine Learning Algorithms: Adversarial Robustness in Signal Processing Li Fuwei

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This book demonstrates the optimal adversarial attacks against several important signal processing algorithms. Since data quality is crucial in signal processing, the adversary that can poison the data will be a significant threat to signal processing. Through presenting the opti… Celý popis ↓

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Popis Machine Learning Algorithms: Adversarial Robustness in Signal Processing Li Fuwei

Machine Learning Algorithms: Adversarial Robustness in Signal Processing Li Fuwei

This book demonstrates the optimal adversarial attacks against several important signal processing algorithms. Since data quality is crucial in signal processing, the adversary that can poison the data will be a significant threat to signal processing. Through presenting the optimal attacks in wireless sensor networks, array signal processing, principal component analysis, etc, the authors reveal the robustness of the signal processing algorithms against adversarial attacks.

As to linear Therefore, it is necessary and urgent to investigate the behavior of machine learning algorithms in signal processing under adversarial attacks.The authors in this book mainly examine the adversarial robustness of three commonly used machine learning algorithms in signal processing respectively: linear regression, LASSO-based feature selection, and principal component analysis (PCA).

Machine Learning Algorithms: Adversarial Robustness in Signal Processing Li Fuwei patrí medzi produkty, ktoré ponúkajú vyvážený pomer kvality a ceny. V hornej časti stránky nájdeš hlavný prehľad, nižšie podrobné vlastnosti a technické parametre.

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