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Moritz Hardt
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Cited by
Year
Understanding deep learning requires rethinking generalization
C Zhang, S Bengio, M Hardt, B Recht, O Vinyals
ICLR 2017, 2017
7587*2017
Equality of opportunity in supervised learning
M Hardt, E Price, N Srebro
NIPS 2016, 3315-3323, 2016
50862016
Fairness through awareness
C Dwork, M Hardt, T Pitassi, O Reingold, R Zemel
ITCS 2012, 214-226, 2012
45202012
Sanity checks for saliency maps
J Adebayo, J Gilmer, M Muelly, I Goodfellow, M Hardt, B Kim
NeurIPS 2018, 2018
23652018
Fairness and machine learning: Limitations and Opportunities
S Barocas, M Hardt, A Narayanan
MIT Press, 2023
2157*2023
Train faster, generalize better: Stability of stochastic gradient descent
M Hardt, B Recht, Y Singer
ICML 2016, 1225-1234, 2015
14552015
Test-time training with self-supervision for generalization under distribution shifts
Y Sun, X Wang, Z Liu, J Miller, A Efros, M Hardt
ICML 2020, 9229-9248, 2020
8422020
Avoiding discrimination through causal reasoning
N Kilbertus, MR Carulla, G Parascandolo, M Hardt, D Janzing, ...
NIPS 2017, 656-666, 2017
7322017
A system for massively parallel hyperparameter tuning
L Li, K Jamieson, A Rostamizadeh, E Gonina, M Hardt, B Recht, ...
arXiv preprint arXiv:1810.05934, 2018
639*2018
A simple and practical algorithm for differentially private data release
M Hardt, K Ligett, F McSherry
NIPS 2012, 2348-2356, 2012
5802012
Delayed impact of fair machine learning
LT Liu, S Dean, E Rolf, M Simchowitz, M Hardt
ICML 2018, 2018
5642018
A multiplicative weights mechanism for privacy-preserving data analysis
M Hardt, GN Rothblum
FOCS 2010, 61-70, 2010
5082010
On the geometry of differential privacy
M Hardt, K Talwar
STOC 2010, 705-714, 2010
5052010
Retiring Adult: New datasets for fair machine learning
F Ding, M Hardt, J Miller, L Schmidt
Advances in Neural Information Processing Systems 34, 2021
4512021
Identity matters in deep learning
M Hardt, T Ma
ICLR 2017, 2017
4452017
Strategic classification
M Hardt, N Megiddo, C Papadimitriou, M Wootters
ITCS 2016, 111-122, 2016
4352016
Preserving statistical validity in adaptive data analysis
C Dwork, V Feldman, M Hardt, T Pitassi, O Reingold, A Roth
STOC 2015, 2014
4202014
The reusable holdout: Preserving validity in adaptive data analysis
C Dwork, V Feldman, M Hardt, T Pitassi, O Reingold, A Roth
Science 349 (6248), 636-638, 2015
4022015
Performative prediction
JC Perdomo, T Zrnic, C Mendler-Dünner, M Hardt
ICML 2020, 2020
3722020
Gradient descent learns linear dynamical systems
M Hardt, T Ma, B Recht
Journal of Machine Learning Research 19, 1-44, 2018
3582018
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Articles 1–20