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Subverting Fair Image Search with Generative Adversarial Perturbations

Offered By: Association for Computing Machinery (ACM) via YouTube

Tags

ACM FAccT Conference Courses Machine Learning Courses

Course Description

Overview

Explore the intricacies of manipulating fair image search algorithms through generative adversarial perturbations in this 15-minute conference talk presented at an Association for Computing Machinery (ACM) event. Delve into the concepts of fair ranking and intentional bias as speakers Avijit Ghosh, Matthew Jagielski, and Christo Wilson guide you through their innovative methods and experiments. Gain insights into the potential vulnerabilities of fair image search systems and understand the implications of their groundbreaking results in this thought-provoking presentation on the intersection of artificial intelligence, fairness, and image search technology.

Syllabus

Introduction
Fair Ranking
Intentional Bias
Methods
Experiments
Results


Taught by

ACM FAccT Conference

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