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Bridging Machine Learning and Mechanism Design towards Algorithmic Fairness

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

Tags

ACM FAccT Conference Courses Machine Learning Courses Algorithmic Decision-Making Courses Algorithmic Fairness Courses

Course Description

Overview

Explore a conference talk that delves into the intersection of machine learning and mechanism design to address algorithmic fairness. Discover how researchers J. Finocchiaro, R. Maio, F. Monachou, G. Patro, M. Raghavan, A. Stoica, and S. Tsirtsis present their findings on bridging these two fields to create more equitable algorithmic systems. Learn about the latest developments in this crucial area of study, presented at the FAccT 2021 virtual conference. Gain insights into the challenges and potential solutions for implementing fairness in machine learning algorithms and mechanism design. This 19-minute presentation, part of the Research Track, offers a concise yet comprehensive overview of the topic, making it an essential watch for those interested in the ethical implications of AI and machine learning.

Syllabus

Bridging Machine Learning and Mechanism Design towards Algorithmic Fairness


Taught by

ACM FAccT Conference

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