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Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies
Language: en
Pages: 83
Authors: National Academies of Sciences, Engineering, and Medicine
Categories: Computers
Type: BOOK - Published: 2019-08-22 - Publisher: National Academies Press

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The Intelligence Community Studies Board (ICSB) of the National Academies of Sciences, Engineering, and Medicine convened a workshop on December 11â€"12, 201
Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies
Language: en
Pages: 83
Authors: National Academies of Sciences, Engineering, and Medicine
Categories: Computers
Type: BOOK - Published: 2019-08-22 - Publisher: National Academies Press

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The Intelligence Community Studies Board (ICSB) of the National Academies of Sciences, Engineering, and Medicine convened a workshop on December 11â€"12, 201
Adversarial Machine Learning
Language: en
Pages: 341
Authors: Anthony D. Joseph
Categories: Computers
Type: BOOK - Published: 2019-02-21 - Publisher: Cambridge University Press

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Written by leading researchers, this complete introduction brings together all the theory and tools needed for building robust machine learning in adversarial e
Machine Learning Algorithms
Language: en
Pages: 109
Authors: Fuwei Li
Categories: Computers
Type: BOOK - Published: 2022-11-14 - Publisher: Springer Nature

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This book demonstrates the optimal adversarial attacks against several important signal processing algorithms. Through presenting the optimal attacks in wireles
Studying the Robustness of Machine Learning-based Malware Detection Models
Language: en
Pages: 0
Authors: Ahmed Abusnaina
Categories:
Type: BOOK - Published: 2022 - Publisher:

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With the rise of the popularity of machine learning (ML), it has been shown that ML-based classifiers are susceptible to adversarial examples and concept drifti