Distill-and-Compare
Author:
Affiliation:
1. Cornell University, Ithaca, NY, USA
2. Microsoft Research, Redmond, WA, USA
3. Ant Financial, San Mateo, CA, USA
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3278721.3278725
Reference36 articles.
1. Philip Adler Casey Falk Sorelle A. Friedler Gabriel Rybeck Carlos Eduardo Scheidegger Brandon Smith and Suresh Venkatasubramanian. 2016. Auditing Black-Box Models for Indirect Influence. In ICDM . Philip Adler Casey Falk Sorelle A. Friedler Gabriel Rybeck Carlos Eduardo Scheidegger Brandon Smith and Suresh Venkatasubramanian. 2016. Auditing Black-Box Models for Indirect Influence. In ICDM .
2. Alekh Agarwal Alina Beygelzimer Miroslav Dudik John Langford and Hanna Wallach. 2018. A reductions approach to fair classification. In ICML . Alekh Agarwal Alina Beygelzimer Miroslav Dudik John Langford and Hanna Wallach. 2018. A reductions approach to fair classification. In ICML .
3. Julia Angwin Jeff Larson Surya Mattu and Lauren Kirchner. 2016a. How we analyzed the compas recidivism algorithm. https://www.propublica.org/article/how-we-analyzed-the-compas-recidivism-algorithm Accessed May 26 2017. Julia Angwin Jeff Larson Surya Mattu and Lauren Kirchner. 2016a. How we analyzed the compas recidivism algorithm. https://www.propublica.org/article/how-we-analyzed-the-compas-recidivism-algorithm Accessed May 26 2017.
4. Julia Angwin Jeff Larson Surya Mattu and Lauren Kirchner. 2016b. Machine Bias: There's software used across the country to predict future criminals. And it's biased against blacks. https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing Accessed May 26 2017. Julia Angwin Jeff Larson Surya Mattu and Lauren Kirchner. 2016b. Machine Bias: There's software used across the country to predict future criminals. And it's biased against blacks. https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing Accessed May 26 2017.
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