Completed
Fairness in Machine Learning
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
Fairness in Representation Learning - Natalie Dullerud
Automatically move to the next video in the Classroom when playback concludes
- 1 Fairness in Representation Learning A study in evaluation and mitigation of bias via subgroup
- 2 Fairness in Machine Learning
- 3 Fairness in Representations: DML
- 4 Overview: Fairness in Deep Metric Learning
- 5 Intuition: Fairness in DML
- 6 Defining Fairness in DML
- 7 Experimental Design
- 8 Empirical Results: Bias Propagates
- 9 Bias Mitigation: Considerations
- 10 Bias Mitigation: An Initial Solution (PARADE)
- 11 Empirical Results in PARADE
- 12 Comparison with Oversampling
- 13 Limitations to PARADE
- 14 Fairness Improvements in Representations
- 15 Thank you for listening!
- 16 PARtial Attribute DE-correlation (PARADE)
