What can we learn privately? SP Kasiviswanathan, HK Lee, K Nissim, S Raskhodnikova, A Smith SIAM Journal on Computing 40 (3), 793-826, 2011 | 1508 | 2011 |
Composition attacks and auxiliary information in data privacy SR Ganta, SP Kasiviswanathan, A Smith Proceedings of the 14th ACM SIGKDD international conference on Knowledge …, 2008 | 503 | 2008 |
Analyzing graphs with node differential privacy SP Kasiviswanathan, K Nissim, S Raskhodnikova, A Smith Theory of Cryptography: 10th Theory of Cryptography Conference, TCC 2013 …, 2013 | 396 | 2013 |
Subsampled rényi differential privacy and analytical moments accountant YX Wang, B Balle, SP Kasiviswanathan The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 365 | 2019 |
Simple Black-Box Adversarial Attacks on Deep Neural Networks. N Narodytska, SP Kasiviswanathan CVPR Workshops 2, 2, 2017 | 341 | 2017 |
Simple black-box adversarial perturbations for deep networks N Narodytska, SP Kasiviswanathan arXiv preprint arXiv:1612.06299, 2016 | 266 | 2016 |
Verifying properties of binarized deep neural networks N Narodytska, S Kasiviswanathan, L Ryzhyk, M Sagiv, T Walsh Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 262 | 2018 |
Bounds on the sample complexity for private learning and private data release A Beimel, H Brenner, SP Kasiviswanathan, K Nissim Machine learning 94, 401-437, 2014 | 238 | 2014 |
Private spatial data aggregation in the local setting R Chen, H Li, AK Qin, SP Kasiviswanathan, H Jin 2016 IEEE 32nd International Conference on Data Engineering (ICDE), 289-300, 2016 | 186 | 2016 |
On the'semantics' of differential privacy: A bayesian formulation SP Kasiviswanathan, A Smith Journal of Privacy and Confidentiality 6 (1), 2014 | 184 | 2014 |
Emerging topic detection using dictionary learning SP Kasiviswanathan, P Melville, A Banerjee, V Sindhwani Proceedings of the 20th ACM international conference on Information and …, 2011 | 170 | 2011 |
The price of privately releasing contingency tables and the spectra of random matrices with correlated rows SP Kasiviswanathan, M Rudelson, A Smith, J Ullman Proceedings of the forty-second ACM symposium on Theory of computing, 775-784, 2010 | 128 | 2010 |
A note on differential privacy: Defining resistance to arbitrary side information SP Kasiviswanathan, A Smith CoRR abs/0803.3946, 2008 | 108 | 2008 |
Algorithms for Counting 2-Sat Solutions and Colorings with Applications M Fürer, SP Kasiviswanathan Algorithmic Aspects in Information and Management: Third International …, 2007 | 78 | 2007 |
Efficient and practical stochastic subgradient descent for nuclear norm regularization H Avron, S Kale, S Kasiviswanathan, V Sindhwani arXiv preprint arXiv:1206.6384, 2012 | 76 | 2012 |
Efficient private empirical risk minimization for high-dimensional learning SP Kasiviswanathan, H Jin International Conference on Machine Learning, 488-497, 2016 | 69 | 2016 |
Online l1-dictionary learning with application to novel document detection S Kasiviswanathan, H Wang, A Banerjee, P Melville Advances in neural information processing systems 25, 2012 | 67 | 2012 |
Federated learning under arbitrary communication patterns D Avdiukhin, S Kasiviswanathan International Conference on Machine Learning, 425-435, 2021 | 61 | 2021 |
Semi-supervised learning on data streams via temporal label propagation T Wagner, S Guha, S Kasiviswanathan, N Mishra International Conference on Machine Learning, 5095-5104, 2018 | 59 | 2018 |
Streaming anomaly detection using randomized matrix sketching H Huang, SP Kasiviswanathan Proceedings of the VLDB Endowment 9 (3), 192-203, 2015 | 59 | 2015 |