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Sorelle A. Friedler
Sorelle A. Friedler
Associate Professor of Computer Science, Haverford College
Verified email at haverford.edu - Homepage
Title
Cited by
Cited by
Year
Certifying and removing disparate impact
M Feldman, SA Friedler, J Moeller, C Scheidegger, ...
proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015
14592015
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
10672016
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
5672019
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
4682019
On the (im) possibility of fairness
SA Friedler, C Scheidegger, S Venkatasubramanian
arXiv preprint arXiv:1609.07236, 2016
3852016
Runaway feedback loops in predictive policing
D Ensign, SA Friedler, S Neville, C Scheidegger, S Venkatasubramanian
Conference on Fairness, Accountability, and Transparency, 2018
3322018
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
3162018
Problems with Shapley-value-based explanations as feature importance measures
IE Kumar, S Venkatasubramanian, C Scheidegger, S Friedler
International Conference on Machine Learning, 5491-5500, 2020
2032020
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
1182019
The (im) possibility of fairness: Different value systems require different mechanisms for fair decision making
SA Friedler, C Scheidegger, S Venkatasubramanian
Communications of the ACM 64 (4), 136-143, 2021
842021
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
582016
Hiring by algorithm: predicting and preventing disparate impact
I Ajunwa, S Friedler, CE Scheidegger, S Venkatasubramanian
Available at SSRN 2746078, 2016
572016
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
562019
How to hold algorithms accountable
N Diakopoulos, S Friedler
MIT Technology Review 17 (11), 2016, 2016
492016
Fairness Warnings and Fair-MAML: Learning Fairly with Minimal Data
D Slack, S Friedler, E Givental
Conference on Fairness, Accountability, and Transparency, 2020
422020
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
422019
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
352019
Automated congressional redistricting
HA Levin, SA Friedler
Journal of Experimental Algorithmics (JEA) 24, 1-24, 2019
312019
Assessing the Local Interpretability of Machine Learning Models
D Slack, SA Friedler, C Scheidegger, CD Roy
NeurIPS Workshop on Human-Centric Machine Learning, 2019
312019
Assessing the local interpretability of machine learning models
SA Friedler, CD Roy, C Scheidegger, D Slack
282019
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