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Everything about Adversarial machine learning
Research field that lies at the intersection of machine learning and computer security
Adversarial machine learning is the study of the attacks on machine learning algorithms, and of the defenses against such attacks. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Adversarial machine learningA 5-minute orientation
- Skim a recent paper: Machine Learning in NextG Networks via Generative Adversarial NetworksInfluential work since 2022
- Pick up a classic book: Artificial intelligenceThe most-reprinted book on the subject
- Read the landmark paper: Adversarial attacks on medical machine learningCited 951 times
- Go sideways: Concept driftA closely related topic
- Go sideways: Self-supervised learningA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
Adversarial attacks on medical machine learning
Distributed Statistical Machine Learning in Adversarial Settings
Making machine learning robust against adversarial inputs
Adversarial machine learning in Network Intrusion Detection Systems
Quantum adversarial machine learning
Machine Learning in Adversarial Settings
Towards quantum enhanced adversarial robustness in machine learning
Defense strategies for Adversarial Machine Learning: A survey
🆕 Influential since 2022
Machine Learning in NextG Networks via Generative Adversarial Networks
Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learning
Adversarial Approaches to Tackle Imbalanced Data in Machine Learning
Adversarial Machine Learning in Text Processing: A Literature Survey
Adversarial Machine Learning: Bayesian Perspectives
📚 Books worth reading
Artificial intelligenceStuart J. Russell, Peter Norvig · 1994
The Frontiers of ManagementPeter F. Drucker · 1986
Winsor McCayWinsor McCay · 2003
Adversarial Machine LearningYevgeniy Vorobeychik, Murat Kantarcioglu · 2018- 📕Generative Adversarial Networks and Super ResolutionManish Jain, Dinesh Sethi · 2022
Adversarial Machine LearningAnthony D. Joseph, Blaine Nelson · 2017- 📕Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and AnomaliesNational Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences · 2019
- 📕Machine Learning AlgorithmsFuwei Li, Lifeng Lai · 2022
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
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