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Raef Bassily
Raef Bassily
Associate Professor, Computer Science & Engineering, The Ohio State University
Verifierad e-postadress på osu.edu - Startsida
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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
10892014
Local, private, efficient protocols for succinct histograms
R Bassily, A Smith
Proceedings of the forty-seventh annual ACM symposium on Theory of computing …, 2015
5632015
The power of interpolation: Understanding the effectiveness of SGD in modern over-parametrized learning
S Ma, R Bassily, M Belkin
International Conference on Machine Learning, 3325-3334, 2018
3522018
Practical locally private heavy hitters
R Bassily, K Nissim, U Stemmer, A Guha Thakurta
Advances in Neural Information Processing Systems 30, 2017
3122017
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
3092016
Private stochastic convex optimization with optimal rates
R Bassily, V Feldman, K Talwar, A Guha Thakurta
Advances in neural information processing systems 32, 2019
2822019
Cooperative security at the physical layer: A summary of recent advances
R Bassily, E Ekrem, X He, E Tekin, J Xie, MR Bloch, S Ulukus, A Yener
IEEE Signal Processing Magazine 30 (5), 16-28, 2013
2402013
Stability of stochastic gradient descent on nonsmooth convex losses
R Bassily, V Feldman, C Guzmán, K Talwar
Advances in Neural Information Processing Systems 33, 4381-4391, 2020
2182020
On exponential convergence of sgd in non-convex over-parametrized learning
R Bassily, M Belkin, S Ma
arXiv preprint arXiv:1811.02564, 2018
1202018
Learners that use little information
R Bassily, S Moran, I Nachum, J Shafer, A Yehudayoff
Algorithmic Learning Theory, 25-55, 2018
1192018
Coupled-worlds privacy: Exploiting adversarial uncertainty in statistical data privacy
R Bassily, A Groce, J Katz, A Smith
2013 IEEE 54th Annual Symposium on Foundations of Computer Science, 439-448, 2013
1132013
Differentially private empirical risk minimization: Efficient algorithms and tight error bounds
R Bassily, A Smith, A Thakurta
arXiv preprint arXiv:1405.7085, 2014
842014
Model-agnostic private learning
R Bassily, O Thakkar, A Guha Thakurta
Advances in neural information processing systems 31, 2018
832018
Non-euclidean differentially private stochastic convex optimization
R Bassily, C Guzmán, A Nandi
Conference on Learning Theory, 474-499, 2021
792021
Limits of private learning with access to public data
N Alon, R Bassily, S Moran
Advances in neural information processing systems 32, 2019
712019
Deaf cooperation and relay selection strategies for secure communication in multiple relay networks
R Bassily, S Ulukus
IEEE Transactions on Signal Processing 61 (6), 1544-1554, 2012
682012
Private query release assisted by public data
R Bassily, A Cheu, S Moran, A Nikolov, J Ullman, S Wu
International Conference on Machine Learning, 695-703, 2020
662020
Differentially private stochastic optimization: New results in convex and non-convex settings
R Bassily, C Guzmán, M Menart
Advances in Neural Information Processing Systems 34, 9317-9329, 2021
592021
Linear queries estimation with local differential privacy
R Bassily
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
582019
Ergodic secret alignment
R Bassily, S Ulukus
IEEE Transactions on Information Theory 58 (3), 1594-1611, 2011
522011
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Artiklar 1–20