Abhradeep Guha Thakurta
Title
Cited by
Cited by
Year
Private empirical risk minimization: Efficient algorithms and tight error bounds
R Bassily, A Smith, A Thakurta
2014 IEEE 55th Annual Symposium on Foundations of Computer Science, 464-473, 2014
2692014
Discovering frequent patterns in sensitive data
R Bhaskar, S Laxman, A Smith, A Thakurta
Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010
2332010
GUPT: privacy preserving data analysis made easy
P Mohan, A Thakurta, E Shi, D Song, D Culler
Proceedings of the 2012 ACM SIGMOD International Conference on Management of …, 2012
2232012
Private convex empirical risk minimization and high-dimensional regression
D Kifer, A Smith, A Thakurta
Conference on Learning Theory, 25.1-25.40, 2012
2022012
Analyze gauss: optimal bounds for privacy-preserving principal component analysis
C Dwork, K Talwar, A Thakurta, L Zhang
Proceedings of the forty-sixth annual ACM symposium on Theory of computing …, 2014
1412014
Differentially private online learning
P Jain, P Kothari, A Thakurta
Conference on Learning Theory, 24.1-24.34, 2012
1352012
Differentially private feature selection via stability arguments, and the robustness of the lasso
AG Thakurta, A Smith
Conference on Learning Theory, 819-850, 2013
972013
Practical locally private heavy hitters
R Bassily, K Nissim, U Stemmer, AG Thakurta
Advances in Neural Information Processing Systems, 2288-2296, 2017
872017
Differentially private learning with kernels
P Jain, A Thakurta
812013
Is interaction necessary for distributed private learning?
A Smith, A Thakurta, J Upadhyay
2017 IEEE Symposium on Security and Privacy (SP), 58-77, 2017
652017
Noiseless database privacy
R Bhaskar, A Bhowmick, V Goyal, S Laxman, A Thakurta
International Conference on the Theory and Application of Cryptology and …, 2011
632011
Nearly optimal private lasso
K Talwar, AG Thakurta, L Zhang
Advances in Neural Information Processing Systems, 3025-3033, 2015
592015
Amplification by shuffling: From local to central differential privacy via anonymity
Ú Erlingsson, V Feldman, I Mironov, A Raghunathan, K Talwar, ...
Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete …, 2019
422019
Private empirical risk minimization, revisited
R Bassily, A Smith, A Thakurta
rem 3, 19, 2014
332014
Privacy amplification by iteration
V Feldman, I Mironov, K Talwar, A Thakurta
2018 IEEE 59th Annual Symposium on Foundations of Computer Science (FOCS …, 2018
282018
Emoji frequency detection and deep link frequency
AG Thakurta, AH Vyrros, US Vaishampayan, G Kapoor, J Freudinger, ...
US Patent 9,705,908, 2017
262017
Learning new words
AG Thakurta, AH Vyrros, US Vaishampayan, G Kapoor, J Freudiger, ...
US Patent 9,594,741, 2017
262017
Private empirical risk minimization beyond the worst case: The effect of the constraint set geometry
K Talwar, A Thakurta, L Zhang
arXiv preprint arXiv:1411.5417, 2014
262014
To drop or not to drop: Robustness, consistency and differential privacy properties of dropout
P Jain, V Kulkarni, A Thakurta, O Williams
arXiv preprint arXiv:1503.02031, 2015
192015
Towards practical differentially private convex optimization
R Iyengar, JP Near, D Song, O Thakkar, A Thakurta, L Wang
2019 IEEE Symposium on Security and Privacy (SP), 299-316, 2019
182019
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