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Adversarial Machine Learning

(ADV-ML.AU1)
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1

Preface

2

Adversarial Machine Learning

  • Adversarial Learning Frameworks
  • Adversarial Security Mechanisms
  • Stochastic Game Illustration in Adversarial Deep Learning
3

Adversarial Deep Learning

  • Learning Curve Analysis for Supervised Machine Learning
  • Adversarial Loss Functions for Discriminative Learning
  • Adversarial Examples in Deep Networks
  • Adversarial Examples for Misleading Classifiers
  • Generative Adversarial Networks
  • Generative Adversarial Networks for Adversarial Learning
  • Transfer Learning for Domain Adaptation
4

Adversarial Attack Surfaces

  • Security and Privacy in Adversarial Learning
  • Feature Weighting Attacks
  • Poisoning Support Vector Machines
  • Robust Classifier Ensembles
  • Robust Clustering Models
  • Robust Feature Selection Models
  • Robust Anomaly Detection Models
  • Robust Task Relationship Models
  • Robust Regression Models
  • Adversarial Machine Learning in Cybersecurity
5

Game Theoretical Adversarial Deep Learning

  • Game Theoretical Learning Models
  • Game Theoretical Adversarial Learning
  • Game Theoretical Adversarial Deep Learning
  • Stochastic Games in Predictive Modeling
  • Robust Game Theory in Adversarial Learning Games
6

Adversarial Defense Mechanisms for Supervised Learning

  • Securing Classifiers Against Feature Attacks
  • Adversarial Classification Tasks with Regularizers
  • Adversarial Reinforcement Learning
  • Computational Optimization Algorithmics for Game Theoretical Adversarial Learning
  • Defense Mechanisms in Adversarial Machine Learning
7

Physical World Adversarial Attacks on Images and Texts

  • Adversarial Attacks on Images
  • Adversarial Attacks on Texts
  • Spam Filtering
8

Adversarial Perturbation for Privacy Preservation

  • Adversarial Perturbation for Privacy Preservation

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