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Balancing utility and scalability in metric differential privacy.

, , , , and . UAI, volume 180 of Proceedings of Machine Learning Research, page 885-894. PMLR, (2022)

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Locally Differentially Private Analysis of Graph Statistics., , and . CoRR, (2020)Privacy Amplification Via Bernoulli Sampling., and . CoRR, (2021)Robustness of Locally Differentially Private Graph Analysis Against Poisoning., , and . CoRR, (2022)No-Substitution $k$-means Clustering with Low Center Complexity and Memory., and . CoRR, (2021)Communication-Efficient Triangle Counting under Local Differential Privacy., , and . USENIX Security Symposium, page 537-554. USENIX Association, (2022)Private estimation algorithms for stochastic block models and mixture models., , , , , , and . CoRR, (2023)Balancing utility and scalability in metric differential privacy., , , , and . UAI, volume 180 of Proceedings of Machine Learning Research, page 885-894. PMLR, (2022)Differentially Private Hierarchical Clustering with Provable Approximation Guarantees., , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 14353-14375. PMLR, (2023)Capacity Bounded Differential Privacy., , and . NeurIPS, page 3469-3478. (2019)Online k-means Clustering on Arbitrary Data Streams., , , and . ALT, volume 201 of Proceedings of Machine Learning Research, page 204-236. PMLR, (2023)