Abhradeep Guha Thakurta
TitleCited byYear
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
2002010
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
1802012
Private convex empirical risk minimization and high-dimensional regression
D Kifer, A Smith, A Thakurta
Conference on Learning Theory, 25.1-25.40, 2012
1342012
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
1332014
Differentially private online learning
P Jain, P Kothari, A Thakurta
Conference on Learning Theory, 24.1-24.34, 2012
1002012
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
952014
Differentially private feature selection via stability arguments, and the robustness of the lasso
AG Thakurta, A Smith
Conference on Learning Theory, 819-850, 2013
712013
Differentially private learning with kernels
P Jain, A Thakurta
632013
Noiseless database privacy
R Bhaskar, A Bhowmick, V Goyal, S Laxman, A Thakurta
International Conference on the Theory and Application of Cryptology and …, 2011
502011
Practical locally private heavy hitters
R Bassily, K Nissim, U Stemmer, AG Thakurta
Advances in Neural Information Processing Systems, 2288-2296, 2017
402017
Differentially private empirical risk minimization: Efficient algorithms and tight error bounds
R Bassily, A Smith, A Thakurta
arXiv preprint arXiv:1405.7085, 2014
332014
Is interaction necessary for distributed private learning?
A Smith, A Thakurta, J Upadhyay
2017 IEEE Symposium on Security and Privacy (SP), 58-77, 2017
292017
Nearly optimal private lasso
K Talwar, AG Thakurta, L Zhang
Advances in Neural Information Processing Systems, 3025-3033, 2015
272015
Private empirical risk minimization, revisited
R Bassily, A Smith, A Thakurta
arXiv preprint arXiv:1405.7085, 2014
232014
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
172015
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
162014
Testing the Lipschitz property over product distributions with applications to data privacy
K Dixit, M Jha, S Raskhodnikova, A Thakurta
Theory of Cryptography, 418-436, 2013
162013
Learning new words
AG Thakurta, AH Vyrros, US Vaishampayan, G Kapoor, J Freudiger, ...
US Patent 9,594,741, 2017
142017
(Near) dimension independent risk bounds for differentially private learning
P Jain, AG Thakurta
International Conference on Machine Learning, 476-484, 2014
102014
(Nearly) optimal algorithms for private online learning in full-information and bandit settings
AG Thakurta, A Smith
Advances in Neural Information Processing Systems, 2733-2741, 2013
92013
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Articles 1–20