Certifying and removing disparate impact M Feldman, SA Friedler, J Moeller, C Scheidegger, ... proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015 | 781 | 2015 |
Machine-learning-assisted materials discovery using failed experiments P Raccuglia, KC Elbert, PDF Adler, C Falk, MB Wenny, A Mollo, M Zeller, ... Nature 533 (7601), 73-76, 2016 | 618 | 2016 |
On the (im) possibility of fairness SA Friedler, C Scheidegger, S Venkatasubramanian arXiv preprint arXiv:1609.07236, 2016 | 217 | 2016 |
Auditing black-box models for indirect influence P Adler, C Falk, SA Friedler, T Nix, G Rybeck, C Scheidegger, B Smith, ... Knowledge and Information Systems 54 (1), 95-122, 2018 | 203* | 2018 |
A comparative study of fairness-enhancing interventions in machine learning SA Friedler, C Scheidegger, S Venkatasubramanian, S Choudhary, ... Proceedings of the conference on fairness, accountability, and transparency …, 2019 | 186 | 2019 |
Fairness and abstraction in sociotechnical systems AD Selbst, D Boyd, SA Friedler, S Venkatasubramanian, J Vertesi Proceedings of the Conference on Fairness, Accountability, and Transparency …, 2019 | 179 | 2019 |
Runaway feedback loops in predictive policing D Ensign, SA Friedler, S Neville, C Scheidegger, S Venkatasubramanian Conference on Fairness, Accountability, and Transparency, 2018 | 151 | 2018 |
Anthropogenic biases in chemical reaction data hinder exploratory inorganic synthesis X Jia, A Lynch, Y Huang, M Danielson, I Lang’at, A Milder, AE Ruby, ... Nature 573 (7773), 251-255, 2019 | 39 | 2019 |
Principles for accountable algorithms and a social impact statement for algorithms N Diakopoulos, S Friedler, M Arenas, S Barocas, M Hay, B Howe, ... Dagstuhl working group write-up: https://www.fatml.org/resources/principles …, 2016 | 39 | 2016 |
How to hold algorithms accountable N Diakopoulos, S Friedler MIT Technology Review 17 (11), 2016, 2016 | 35 | 2016 |
Hiring by algorithm: predicting and preventing disparate impact I Ajunwa, S Friedler, CE Scheidegger, S Venkatasubramanian Available at SSRN, 2016 | 28 | 2016 |
Enabling teachers to explore grade patterns to identify individual needs and promote fairer student assessment SA Friedler, YL Tan, NJ Peer, B Shneiderman Computers & Education 51 (4), 1467-1485, 2008 | 23 | 2008 |
Interpretable active learning RL Phillips, KH Chang, SA Friedler Conference on Fairness, Accountability, and Transparency, 2018 | 20 | 2018 |
Problems with Shapley-value-based explanations as feature importance measures IE Kumar, S Venkatasubramanian, C Scheidegger, S Friedler arXiv preprint arXiv:2002.11097, 2020 | 19 | 2020 |
Approximation algorithm for the kinetic robust K-center problem SA Friedler, DM Mount Computational Geometry 43 (6-7), 572-586, 2010 | 19 | 2010 |
Experiment Specification, Capture and Laboratory Automation Technology (ESCALATE): a software pipeline for automated chemical experimentation and data management IM Pendleton, G Cattabriga, Z Li, MA Najeeb, SA Friedler, AJ Norquist, ... MRS Communications 9 (3), 846-859, 2019 | 17 | 2019 |
Assessing the Local Interpretability of Machine Learning Models D Slack, SA Friedler, C Scheidegger, CD Roy NeurIPS Workshop on Human-Centric Machine Learning, 2019 | 16* | 2019 |
Gaps in Information Access in Social Networks B Fish, A Bashardoust, D Boyd, S Friedler, C Scheidegger, ... The World Wide Web Conference, 480-490, 2019 | 11 | 2019 |
Fairness in representation: quantifying stereotyping as a representational harm M Abbasi, SA Friedler, C Scheidegger, S Venkatasubramanian Proceedings of the 2019 SIAM International Conference on Data Mining, 801-809, 2019 | 9 | 2019 |
Automated congressional redistricting HA Levin, SA Friedler Journal of Experimental Algorithmics (JEA) 24 (1), 1-24, 2019 | 8 | 2019 |