Is interaction necessary for distributed private learning? A Smith, A Thakurta, J Upadhyay 2017 IEEE Symposium on Security and Privacy (SP), 58-77, 2017 | 179 | 2017 |
Near optimal linear algebra in the online and sliding window models V Braverman, P Drineas, C Musco, C Musco, J Upadhyay, DP Woodruff, ... 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS …, 2020 | 63 | 2020 |
Block-wise non-malleable codes N Chandran, V Goyal, P Mukherjee, O Pandey, J Upadhyay Cryptology ePrint Archive, 2015 | 56 | 2015 |
On the complexity of the herding attack and some related attacks on hash functions SR Blackburn, DR Stinson, J Upadhyay Designs, Codes and Cryptography 64, 171-193, 2012 | 56 | 2012 |
On differentially private graph sparsification and applications R Arora, J Upadhyay Advances in neural information processing systems 32, 2019 | 48 | 2019 |
Almost tight error bounds on differentially private continual counting M Henzinger, J Upadhyay, S Upadhyay Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2023 | 29 | 2023 |
The price of privacy for low-rank factorization J Upadhyay Advances in Neural Information Processing Systems 31, 2018 | 29 | 2018 |
Random projections, graph sparsification, and differential privacy J Upadhyay International Conference on the Theory and Application of Cryptology and …, 2013 | 28 | 2013 |
Sublinear space private algorithms under the sliding window model J Upadhyay International Conference on Machine Learning, 6363-6372, 2019 | 23 | 2019 |
Randomness efficient fast-johnson-lindenstrauss transform with applications in differential privacy and compressed sensing J Upadhyay arXiv preprint arXiv:1410.2470, 2014 | 23 | 2014 |
Differentially private linear algebra in the streaming model J Upadhyay arXiv preprint arXiv:1409.5414, 2014 | 23 | 2014 |
Fast and space-optimal low-rank factorization in the streaming model with application in differential privacy J Upadhyay arXiv preprint arXiv:1604.01429, 2016 | 21 | 2016 |
Constant matters: Fine-grained error bound on differentially private continual observation H Fichtenberger, M Henzinger, J Upadhyay International Conference on Machine Learning, 10072-10092, 2023 | 18* | 2023 |
Langevin diffusion: An almost universal algorithm for private euclidean (convex) optimization A Ganesh, A Thakurta, J Upadhyay arXiv preprint arXiv:2204.01585, 2022 | 18 | 2022 |
A coding theory foundation for the analysis of general unconditionally secure proof-of-retrievability schemes for cloud storage MB Paterson, DR Stinson, J Upadhyay Journal of Mathematical Cryptology 7 (3), 183-216, 2013 | 18 | 2013 |
Constant matters: Fine-grained error bound on differentially private continual observation H Fichtenberger, M Henzinger, J Upadhyay International Conference on Machine Learning, 10072-10092, 2023 | 17* | 2023 |
A framework for private matrix analysis in sliding window model J Upadhyay, S Upadhyay International Conference on Machine Learning, 10465-10475, 2021 | 17* | 2021 |
Differentially private analysis on graph streams J Upadhyay, S Upadhyay, R Arora International Conference on Artificial Intelligence and Statistics, 1171-1179, 2021 | 16 | 2021 |
Multi-prover proof of retrievability MB Paterson, DR Stinson, J Upadhyay Journal of Mathematical Cryptology 12 (4), 203-220, 2018 | 16 | 2018 |
Differentially private robust low-rank approximation R Arora, J Upadhyay Advances in neural information processing systems 31, 2018 | 15 | 2018 |