Следене
Seth Neel
Seth Neel
Asst Professor, Harvard University
Потвърден имейл адрес: hbs.edu - Начална страница
Заглавие
Позовавания
Позовавания
Година
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
7332018
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
3192017
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
1792019
Fair algorithms for infinite and contextual bandits
M Joseph, M Kearns, J Morgenstern, S Neel, A Roth
AAAI/AIES 18, 2018
168*2018
Descent-to-delete: Gradient-based methods for machine unlearning
S Neel, A Roth, S Sharifi-Malvajerdi
The 32nd International Conference on Algorithmic Learning Theory, 2021
1392021
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 (NEURIPS 17), 2017
922017
Eliciting and enforcing subjective individual fairness
C Jung, M Kearns, S Neel, A Roth, L Stapleton, ZS Wu
Symposium on Foundations of Responsible Computing (FORC), 2021
86*2021
Adaptive Machine Unlearning
V Gupta, C Jung, S Neel, A Roth, S Sharifi-Malvajerdi, C Waites
NEURIPS 2021, 2021
852021
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
842019
The Role of Interactivity in Local Differential Privacy
M Joseph, J Mao, S Neel, A Roth
Foundations of Computer Science (FOCS 19), 2019
792019
A New Analysis of Differential Privacy's Generalization Guarantees
C Jung, K Ligett, S Neel, A Roth, S Sharifi-Malvajerdi, M Shenfeld
Innovations in Theoretical Computer Science (ITCS), Spotlight, 2020
382020
Mitigating Bias in Adaptive Data Gathering via Differential Privacy
S Neel, A Roth
International Conference on Machine Learning (ICML 18), 2018
332018
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
212014
How to Use Heuristics for Differential Privacy
S Neel, A Roth, SZ Wu
Foundations of Computer Science (FOCS 19), 2018
202018
Oracle efficient private non-convex optimization
S Neel, A Roth, G Vietri, S Wu
International conference on machine learning, 7243-7252, 2020
14*2020
On the Privacy Risks of Algorithmic Recourse
M Pawelczyk, H Lakkaraju, S Neel
AI STATS 2023, 2023
92023
Optimal, Truthful, and Private Securities Lending
E Diana, M Kearns, S Neel, A Roth
ACM Conference on AI in Finance CAIF20, NEURIPS19 Workshop on Robust AI in …, 2020
22020
In-context unlearning: Language models as few shot unlearners
M Pawelczyk, S Neel, H Lakkaraju
arXiv preprint arXiv:2310.07579, 2023
12023
Mahalanobis Matching and Equal Percent Bias Reduction
SV Neel
Harvard College, 2015
12015
Binary Quadratic Forms and the Ideal Class Group
SV Neel
Lecture Notes, Harvard University, 2012
12012
Системата не може да изпълни операцията сега. Опитайте отново по-късно.
Статии 1–20