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Intro
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Classroom Contents
Introduction to Adversarial Attacks in Machine Learning - Lecture 1
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- 1 Intro
- 2 Attacks in the Real World
- 3 Fooling Face Recognition (Impersonation)
- 4 Adversarial Attack on Semantic Segmentation
- 5 Semantic Segmentation and Object Detection
- 6 Changing facial attributes and Gender
- 7 Adversarial attack on mobile phone cameras
- 8 Attack on a 3D-printed turtle
- 9 Attack on 3D Object Detection
- 10 Project Description
- 11 Terminology
- 12 Vector operations
- 13 Norms (Unit Ball)
- 14 Fast Gradient Sign Method (FGSM)
- 15 Momentum Iterative FGSM (MI-FGSM)
- 16 Projected Gradient Descent PGD
- 17 L-BFGS (Limited memory BFGS: Broyden-Fletcher-Goldfarb-Shanno algorithm)
- 18 Carlini and Wagner (C&W)
- 19 DeepFool (Binary Affine Classifier)
- 20 DeepFool (Binary Classifier)
- 21 DeepFool (Multi-Class Classifier)
- 22 Last Two Topics
- 23 Slides Credits
