Sushant Agarwal 个人学术档案

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Shai Ben-DavidUniverity of Waterloo, Canada在 uwaterloo.ca 的电子邮件经过验证
Nivasini AnanthakrishnanUC Berkeley在 berkeley.edu 的电子邮件经过验证
Tosca LechnerPhD student, University of Waterloo在 uwaterloo.ca 的电子邮件经过验证
Ruth UrnerAssociate Professor, York University, Toronto在 eecs.yorku.ca 的电子邮件经过验证
Shahin JabbariDrexel University在 drexel.edu 的电子邮件经过验证
Zhiwei Steven WuCarnegie Mellon University在 andrew.cmu.edu 的电子邮件经过验证
Chirag AgarwalPostdoctoral Research Fellow, Harvard在 hbs.edu 的电子邮件经过验证
Sohini UpadhyayHarvard University在 g.harvard.edu 的电子邮件经过验证
Himabindu LakkarajuAssistant Professor, Harvard University在 seas.harvard.edu 的电子邮件经过验证
Amit DeshpandeMicrosoft Research在 microsoft.com 的电子邮件经过验证

Sushant Agarwal

Northeastern University

在 northeastern.edu 的电子邮件经过验证 - 首页


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Towards the unification and robustness of perturbation and gradient based explanations S Agarwal, S Jabbari, C Agarwal, S Upadhyay, S Wu, H Lakkaraju International Conference on Machine Learning, 110-119, 2021	53	2021
Trade-offs between fairness and privacy in machine learning S Agarwal IJCAI 2021 Workshop on AI for Social Good, 2021	28	2021
On Trade-Offs between Fairness, Interpretability, and Privacy in Classification S Agarwal University of Waterloo, 2020	21*	2020
On Learnability with Computable Learners S Agarwal, N Ananthakrishnan, S Ben-David, T Lechner, R Urner Algorithmic Learning Theory, 48-60, 2020	20	2020
Trade-offs between fairness and interpretability in machine learning S Agarwal IJCAI 2021 Workshop on AI for Social Good, 1-6, 2021	19	2021
Impossibility Results for Fair Representations T Lechner, S Ben-David, S Agarwal, N Ananthakrishnan arXiv preprint arXiv:2107.03483, 2021	13	2021
On the Power of Randomization in Fair Classification and Representation S Agarwal, A Deshpande 2022 ACM Conference on Fairness, Accountability, and Transparency, 1542-1551, 2022	7	2022
Open Problem: Are all VC-classes CPAC Learnable? S Agarwal, N Ananthakrishnan, S Ben-David, T Lechner, R Urner Conference on Learning Theory, 4636-4641, 2021	6	2021
Private Mean Estimation with Person-Level Differential Privacy S Agarwal, G Kamath, M Majid, A Mouzakis, R Silver, J Ullman arXiv preprint arXiv:2405.20405, 2024		2024

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