Or Sheffet
Citeras av
Citeras av
Optimal social choice functions: A utilitarian view
C Boutilier, I Caragiannis, S Haber, T Lu, AD Procaccia, O Sheffet
Artificial Intelligence 227, 190-213, 2015
The johnson-lindenstrauss transform itself preserves differential privacy
J Blocki, A Blum, A Datta, O Sheffet
2012 IEEE 53rd Annual Symposium on Foundations of Computer Science, 410-419, 2012
Differentially private data analysis of social networks via restricted sensitivity
J Blocki, A Blum, A Datta, O Sheffet
Proceedings of the 4th conference on Innovations in Theoretical Computer …, 2013
Center-based clustering under perturbation stability
P Awasthi, A Blum, O Sheffet
Information Processing Letters 112 (1-2), 49-54, 2012
Improved spectral-norm bounds for clustering
P Awasthi, O Sheffet
Approximation, Randomization, and Combinatorial Optimization. Algorithms and …, 2012
Disposable intraocular lens insertion system
V Feingold, DC Eagles
US Patent 6,921,405, 2005
Stability yields a PTAS for k-median and k-means clustering
P Awasthi, A Blum, O Sheffet
2010 IEEE 51st Annual Symposium on Foundations of Computer Science, 309-318, 2010
Send mixed signals: earn more, work less
P Bro Miltersen, O Sheffet
Proceedings of the 13th ACM Conference on Electronic Commerce, 234-247, 2012
Differentially private ordinary least squares
O Sheffet
International Conference on Machine Learning, 3105-3114, 2017
Learning mixtures of ranking models
P Awasthi, A Blum, O Sheffet, A Vijayaraghavan
Advances in Neural Information Processing Systems 27, 2609-2617, 2014
Psi ({\Psi}): a private data sharing interface
M Gaboardi, J Honaker, G King, J Murtagh, K Nissim, J Ullman, S Vadhan
arXiv preprint arXiv:1609.04340, 2016
Optimizing password composition policies
J Blocki, S Komanduri, A Procaccia, O Sheffet
Proceedings of the fourteenth ACM conference on Electronic commerce, 105-122, 2013
Graph colouring with no large monochromatic components
N Linial, J Matoušek, O Sheffet, GÁ Tardos
Combinatorics, Probability and Computing 17 (4), 577-589, 2008
Locally private hypothesis testing
O Sheffet
arXiv preprint arXiv:1802.03441, 2018
Differentially private contextual linear bandits
R Shariff, O Sheffet
Advances in Neural Information Processing Systems 31, 4296-4306, 2018
Systems and methods for video monitoring using linked devices
I Horovitz, S Kiro, O Sheffet
US Patent 8,531,522, 2013
Locally Private Mean Estimation: -test and Tight Confidence Intervals
M Gaboardi, R Rogers, O Sheffet
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
Old Techniques in Differentially Private Linear Regression
O Sheffet
Algorithmic Learning Theory, 789-827, 2019
On the randomness complexity of property testing
O Goldreich, O Sheffet
Computational Complexity 19 (1), 99-133, 2010
Improved guarantees for agnostic learning of disjunctions
P Awasthi, A Blum, O Sheffet
Carnegie Mellon University, 2010
Systemet kan inte utföra åtgärden just nu. Försök igen senare.
Artiklar 1–20