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Classroom Contents
Fairness and Robustness in Machine Learning – A Formal Methods Perspective - Aditya Nori, Microsoft
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- 1 Introduction
- 2 New programming language challenges
- 3 How does one formalize the notion of fairness
- 4 Algorithmic decision making
- 5 Questions
- 6 Question
- 7 Population model
- 8 Symbolic execution
- 9 Invariants
- 10 Triangle example
- 11 Hyper rectangular decomposition
- 12 Subsampling hyper rectangles
- 13 Challenges with sampling
- 14 Ideal solution
- 15 Approximate density
- 16 Properties
- 17 Proofs
- 18 Summary
