Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics | Paper Citation Record

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Mare c ek, J

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics J., and Vayanos, P

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics P., Schwarting, W., Bhatia, S

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Villeneuve, S

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Weller, A

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics B., Brevoort, K

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Beyond Individual and Group Fairness

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics A New Approach to Learning Linear Dynamical Systems

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Selbst, A

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics H., Burachik, R

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Kohavi, R

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics J., Hammel, E

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Recovering from Biased Data: Can Fairness Constraints Improve Accuracy?

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Quantum open system identification via global optimization: Optimally accurate Markovian models of open systems from time-series data

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics (October 12th, 2023)

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Temam, R

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Reference 81

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Reference 82

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Reference 85

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Projection to Fairness in Statistical Learning

Reference 86

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Reference 87

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Reference 88

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Reference 89

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Reference 97

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Reference 99

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