Seth Neel
Seth Neel
Assistant Professor at Harvard
Verified email at wharton.upenn.edu - Homepage
Title
Cited by
Cited by
Year
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
M Kearns, S Neel, A Roth, ZS Wu
International Conference on Machine Learning (ICML 18), 2018
1782018
A convex framework for fair regression
R Berk, H Heidari, S Jabbari, M Joseph, M Kearns, J Morgenstern, S Neel, ...
Fairness, Accountability, and Transparency in Machine Learning (FATML 17), 2017
752017
Fair algorithms for infinite and contextual bandits
M Joseph, M Kearns, J Morgenstern, S Neel, A Roth
AAAI/AIES 18, 2018
69*2018
An empirical study of rich subgroup fairness for machine learning
M Kearns, S Neel, A Roth, ZS Wu
Conference on Fairness, Accountability, and Transparency (FAT* 19), 2019
362019
Accuracy first: Selecting a differential privacy level for accuracy constrained erm
K Ligett, S Neel, A Roth, B Waggoner, SZ Wu
Advances in Neural Information Processing Systems (NIPS 17), 2017
292017
The Role of Interactivity in Local Differential Privacy
M Joseph, J Mao, S Neel, A Roth
Foundations of Computer Science (FOCS 19), 2019
202019
Fair algorithms for learning in allocation problems
H Elzayn, S Jabbari, C Jung, M Kearns, S Neel, A Roth, Z Schutzman
Conference on Fairness, Accountability, and Transparency (FAT* 19), 2019
182019
Aztec castles and the dP3 quiver
M Leoni, G Musiker, S Neel, P Turner
Journal of Physics A: Mathematical and Theoretical 47 (47), 474011, 2014
172014
Eliciting and enforcing subjective individual fairness
C Jung, M Kearns, S Neel, A Roth, L Stapleton, ZS Wu
arXiv preprint arXiv:1905.10660, 2019
162019
Mitigating Bias in Adaptive Data Gathering via Differential Privacy
S Neel, A Roth
International Conference on Machine Learning (ICML 18), 2018
92018
How to Use Heuristics for Differential Privacy
S Neel, A Roth, SZ Wu
Foundations of Computer Science (FOCS 19), 2018
72018
A New Analysis of Differential Privacy's Generalization Guarantees
C Jung, K Ligett, S Neel, A Roth, S Sharifi-Malvajerdi, M Shenfeld
arXiv preprint arXiv:1909.03577, 2019
62019
Differentially private objective perturbation: Beyond smoothness and convexity
S Neel, A Roth, G Vietri, ZS Wu
arXiv preprint arXiv:1909.01783, 2019
12019
Binary Quadratic Forms and the Ideal Class Group
SV Neel
Lecture Notes, Harvard University, 2012
12012
Optimal, Truthful, and Private Securities Lending
E Diana, M Kearns, S Neel, A Roth
arXiv preprint arXiv:1912.06202, 2019
2019
Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained ERM
S Wu, A Roth, K Ligett, B Waggoner, S Neel
Journal of Privacy and Confidentiality 9 (2), 2019
2019
Mahalanobis Matching and Equal Percent Bias Reduction
SV Neel
Harvard College, 2015
2015
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Articles 1–17