Follow
Uri Stemmer
Title
Cited by
Cited by
Year
Algorithmic stability for adaptive data analysis
R Bassily, K Nissim, A Smith, T Steinke, U Stemmer, J Ullman
Proceedings of the forty-eighth annual ACM symposium on Theory of Computing …, 2016
2582016
Practical locally private heavy hitters
R Bassily, K Nissim, U Stemmer, A Guha Thakurta
Advances in Neural Information Processing Systems 30, 2017
2332017
Differentially private release and learning of threshold functions
M Bun, K Nissim, U Stemmer, S Vadhan
2015 IEEE 56th Annual Symposium on Foundations of Computer Science, 634-649, 2015
1822015
Private learning and sanitization: Pure vs. approximate differential privacy
A Beimel, K Nissim, U Stemmer
Approximation, Randomization, and Combinatorial Optimization. Algorithms and …, 2013
1792013
Heavy hitters and the structure of local privacy
M Bun, J Nelson, U Stemmer
ACM Transactions on Algorithms (TALG) 15 (4), 1-40, 2019
1482019
Characterizing the Sample Complexity of Pure Private Learners.
A Beimel, K Nissim, U Stemmer
J. Mach. Learn. Res. 20, 146:1-146:33, 2019
91*2019
Simultaneous private learning of multiple concepts
M Bun, K Nissim, U Stemmer
Proceedings of the 2016 ACM Conference on Innovations in Theoretical …, 2016
772016
Clustering algorithms for the centralized and local models
K Nissim, U Stemmer
Algorithmic Learning Theory, 619-653, 2018
652018
Privately learning thresholds: Closing the exponential gap
H Kaplan, K Ligett, Y Mansour, M Naor, U Stemmer
Conference on Learning Theory, 2263-2285, 2020
482020
Adversarially robust streaming algorithms via differential privacy
A Hasidim, H Kaplan, Y Mansour, Y Matias, U Stemmer
Advances in Neural Information Processing Systems 33, 147-158, 2020
482020
Differentially private k-means with constant multiplicative error
U Stemmer, H Kaplan
Advances in Neural Information Processing Systems 31, 2018
482018
Locating a small cluster privately
K Nissim, U Stemmer, S Vadhan
Proceedings of the 35th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of …, 2016
452016
Locally private k-means clustering
U Stemmer
The Journal of Machine Learning Research 22 (1), 7964-7993, 2021
442021
On the generalization properties of differential privacy
K Nissim, U Stemmer
arXiv preprint arXiv:1504.05800, 2015
372015
Separating adaptive streaming from oblivious streaming using the bounded storage model
H Kaplan, Y Mansour, K Nissim, U Stemmer
Advances in Cryptology–CRYPTO 2021: 41st Annual International Cryptology …, 2021
31*2021
Learning privately with labeled and unlabeled examples
A Beimel, K Nissim, U Stemmer
Proceedings of the twenty-sixth annual ACM-SIAM symposium on Discrete …, 2014
29*2014
Learning and evaluating a differentially private pre-trained language model
S Hoory, A Feder, A Tendler, S Erell, A Peled-Cohen, I Laish, H Nakhost, ...
Findings of the Association for Computational Linguistics: EMNLP 2021, 1178-1189, 2021
282021
Private center points and learning of halfspaces
A Beimel, S Moran, K Nissim, U Stemmer
Conference on Learning Theory, 269-282, 2019
252019
The limits of post-selection generalization
J Ullman, A Smith, K Nissim, U Stemmer, T Steinke
Advances in Neural Information Processing Systems 31, 2018
202018
A framework for adversarial streaming via differential privacy and difference estimators
I Attias, E Cohen, M Shechner, U Stemmer
arXiv preprint arXiv:2107.14527, 2021
192021
The system can't perform the operation now. Try again later.
Articles 1–20