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Jamie Morgenstern
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Datasheets for datasets
T Gebru, J Morgenstern, B Vecchione, JW Vaughan, H Wallach, HD Iii, ...
Communications of the ACM 64 (12), 86-92, 2021
26522021
Fairness in learning: Classic and contextual bandits
M Joseph, M Kearns, JH Morgenstern, A Roth
Advances in neural information processing systems 29, 325-333, 2016
5632016
A convex framework for fair regression
R Berk, H Heidari, S Jabbari, M Joseph, M Kearns, J Morgenstern, S Neel, ...
FAT/ML 2017, 2017
4202017
Predictive inequity in object detection
B Wilson, J Hoffman, J Morgenstern
arXiv preprint arXiv:1902.11097, 2019
2932019
Fairness in reinforcement learning
S Jabbari, M Joseph, M Kearns, J Morgenstern, A Roth
Proceedings of the 34th International Conference on Machine Learning, 1617-1626, 2016
257*2016
FairVis: Visual analytics for discovering intersectional bias in machine learning
ÁA Cabrera, W Epperson, F Hohman, M Kahng, J Morgenstern, DH Chau
2019 IEEE Conference on Visual Analytics Science and Technology (VAST), 46-56, 2019
2482019
On the pseudo-dimension of nearly optimal auctions
JH Morgenstern, T Roughgarden
Advances in Neural Information Processing Systems 28, 136-144, 2015
2172015
Guarantees for spectral clustering with fairness constraints
M Kleindessner, S Samadi, P Awasthi, J Morgenstern
Proceedings of the 36th International Conference on Machine Learning, 2019
2052019
On the compatibility of privacy and fairness
R Cummings, V Gupta, D Kimpara, J Morgenstern
Adjunct publication of the 27th conference on user modeling, adaptation and …, 2019
2042019
Fair k-center clustering for data summarization
M Kleindessner, P Awasthi, J Morgenstern
Proceedings of the 36th International Conference on Machine Learning (ICML …, 2019
2042019
Meritocratic fairness for infinite and contextual bandits
M Joseph, M Kearns, J Morgenstern, S Neel, A Roth
Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 158-163, 2016
193*2016
The Price of Fair PCA: One Extra Dimension
S Samadi, U Tantipongpipat, J Morgenstern, M Singh, S Vempala
Conference on Neural Information Processing Systems (NIPS) 2018, 2018
1862018
Learning Simple Auctions
J Morgenstern, T Roughgarden
COLT 2016, 1298-1318, 2016
1522016
A smoothed analysis of the greedy algorithm for the linear contextual bandit problem
S Kannan, JH Morgenstern, A Roth, B Waggoner, ZS Wu
Advances in neural information processing systems 31, 2231–2241, 2018
1222018
Diversity and inclusion metrics in subset selection
M Mitchell, D Baker, N Moorosi, E Denton, B Hutchinson, A Hanna, ...
Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 117-123, 2020
1212020
Equalized odds postprocessing under imperfect group information
P Awasthi, M Kleindessner, J Morgenstern
International conference on artificial intelligence and statistics, 1770-1780, 2020
1112020
How bad is selfish voting?
S Brânzei, I Caragiannis, J Morgenstern, A Procaccia
Proceedings of the AAAI conference on artificial intelligence 27 (1), 138-144, 2013
962013
Impartial Peer Review
D Kurokawa, O Lev, J Morgenstern, A Procaccia
International Joint Conference on Artificial Intelligence 15, 582-588, 2015
862015
Active sampling for min-max fairness
J Abernethy, P Awasthi, M Kleindessner, J Morgenstern, C Russell, ...
Proceedings of the 39th International Conference on Machine Learning 162, 53-65, 2020
75*2020
Evaluating fairness of machine learning models under uncertain and incomplete information
P Awasthi, A Beutel, M Kleindessner, J Morgenstern, X Wang
Proceedings of the 2021 ACM conference on fairness, accountability, and …, 2021
682021
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Artikler 1–20