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Adversarial Machine Learning (Synthesis Lectures on Artificial Intelligence and Machine Learning) by Yevgeniy Vorobeychik; Murat Kantarcioglu is a nonfiction available to read on EtoBox.

What is Adversarial Machine Learning (Synthesis Lectures on Artificial Intelligence and Machine Learning) about?

<p><b>This is a technical overview of the field of adversarial machine learning which has emerged to study vulnerabilities of machine learning approaches in adversarial settings and to develop techniques to make learning robust to adversarial manipulation.</b></p> <p> After reviewing machine learning concepts and approaches, as well as common use cases of these in adversarial settings, we present a general categorization of attacks on machine learning. We then address two major categories of attacks and associated defenses: decision-time attacks, in which an adversary changes the nature of instances seen by a learned model at the time of prediction in order to cause errors, and poisoning or training time attacks, in which the actual training dataset is maliciously modified. In our final chapter devoted to technical content, we discuss recent techniques for attacks on deep learning, as well as approaches for improving robustness of deep neural networks. We conclude with a discussion of several important issues in the area of adversarial learning that in our view warrant further research.</p> <p> The increasing abundance of large high-quality datasets, combined with significant techn

Who reads Adversarial Machine Learning (Synthesis Lectures on Artificial Intelligence and Machine Learning)?

Author

Yevgeniy Vorobeychik; Murat Kantarcioglu

Publisher

Morgan & Claypool Publishers

Published

2018

Language

EN

ISBN

9781681733951

Category

nonfiction

Subjects

Mathematics, Computer Science, Science