# Near Neighbor: Who is the Fairest of Them All?

- Published: 06 Jun 2019

Matt Olfat and Anil Aswani. Convex formulations for fair principal component analysis. arXiv preprint arXiv:1802.03765, 2018.

Geo Pleiss, Manish Raghavan, Felix Wu, Jon Kleinberg, and Kilian Q Weinberger. On fairness and calibration. In Advances in Neural Information Processing Systems, pages 5680{5689, 2017. [OpenAIRE]

Yinian Qi and Mikhail J. Atallah. E cient privacy-preserving k-nearest neighbor search. In 28th IEEE International Conference on Distributed Computing Systems (ICDCS 2008), 17-20 June 2008, Beijing, China, pages 311{319. IEEE Computer Society, 2008. [OpenAIRE]

Gregory Shakhnarovich, Trevor Darrell, and Piotr Indyk. Nearest-neighbor methods in learning and vision: theory and practice (neural information processing). The MIT Press, 2006.

A. Torralba and A. A. Efros. Unbiased look at dataset bias. In CVPR 2011, pages 1521{1528, 2011. [OpenAIRE]

Matt Olfat and Anil Aswani. Convex formulations for fair principal component analysis. arXiv preprint arXiv:1802.03765, 2018.

Geo Pleiss, Manish Raghavan, Felix Wu, Jon Kleinberg, and Kilian Q Weinberger. On fairness and calibration. In Advances in Neural Information Processing Systems, pages 5680{5689, 2017. [OpenAIRE]

Yinian Qi and Mikhail J. Atallah. E cient privacy-preserving k-nearest neighbor search. In 28th IEEE International Conference on Distributed Computing Systems (ICDCS 2008), 17-20 June 2008, Beijing, China, pages 311{319. IEEE Computer Society, 2008. [OpenAIRE]

Gregory Shakhnarovich, Trevor Darrell, and Piotr Indyk. Nearest-neighbor methods in learning and vision: theory and practice (neural information processing). The MIT Press, 2006.

A. Torralba and A. A. Efros. Unbiased look at dataset bias. In CVPR 2011, pages 1521{1528, 2011. [OpenAIRE]