| Locally differentially private analysis of graph statistics J Imola, T Murakami, K Chaudhuri 30th USENIX security symposium (USENIX Security 21), 983-1000, 2021 | 54 | 2021 |
| Capacity bounded differential privacy K Chaudhuri, J Imola, A Machanavajjhala Advances in Neural Information Processing Systems 32, 2019 | 41 | 2019 |
| {Communication-Efficient} Triangle Counting under Local Differential Privacy J Imola, T Murakami, K Chaudhuri 31st USENIX Security Symposium (USENIX Security 22), 537-554, 2022 | 20 | 2022 |
| Private estimation algorithms for stochastic block models and mixture models H Chen, V Cohen-Addad, T d'Orsi, A Epasto, J Imola, D Steurer, S Tiegel arXiv preprint arXiv:2301.04822, 2023 | 9 | 2023 |
| Differentially Private Triangle and 4-Cycle Counting in the Shuffle Model J Imola, T Murakami, K Chaudhuri Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications …, 2022 | 7* | 2022 |
| Privacy amplification via bernoulli sampling J Imola, K Chaudhuri arXiv preprint arXiv:2105.10594, 2021 | 7 | 2021 |
| Robustness of Locally Differentially Private Graph Analysis Against Poisoning J Imola, AR Chowdhury, K Chaudhuri arXiv preprint arXiv:2210.14376, 2022 | 1 | 2022 |
| Balancing utility and scalability in metric differential privacy J Imola, S Kasiviswanathan, S White, A Aggarwal, N Teissier Uncertainty in Artificial Intelligence, 885-894, 2022 | 1 | 2022 |
| Online k-means Clustering on Arbitrary Data Streams R Bhattacharjee, J Imola, M Moshkovitz, S Dasgupta International Conference on Algorithmic Learning Theory, 204-236, 2023 | | 2023 |
| Differentially-Private Hierarchical Clustering with Provable Approximation Guarantees J Imola, A Epasto, M Mahdian, V Cohen-Addad, V Mirrokni arXiv preprint arXiv:2302.00037, 2023 | | 2023 |
| Private Graph Statistics and Algorithms in Modern Applications JJ Imola University of California, San Diego, 2023 | | 2023 |
| No-Substitution k-means Clustering with Low Center Complexity and Memory. R Bhattacharjee, J Imola CoRR, 2021 | | 2021 |
