{"total":17,"rows":[{"id":"2106.07153","title":"Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods","created":"2021-06-14","cited_by_count":59,"area":null},{"id":"2102.08598","title":"Leveraging Public Data for Practical Private Query Release","created":"2021-02-17","cited_by_count":39,"area":null},{"id":"2104.02988","title":"Optimal Algorithms for Differentially Private Stochastic Monotone Variational Inequalities and Saddle-Point Problems","created":"2021-04-07","cited_by_count":17,"area":null},{"id":"2106.00001","title":"Privately Learning Subspaces","created":"2021-05-28","cited_by_count":16,"area":null},{"id":"2305.01177","title":"Unbounded Differentially Private Quantile and Maximum Estimation","created":"2023-05-02","cited_by_count":6,"area":null},{"id":"2306.00920","title":"Better Private Linear Regression Through Better Private Feature Selection","created":"2023-06-01","cited_by_count":5,"area":null},{"id":"2209.07403","title":"Private Stochastic Optimization With Large Worst-Case Lipschitz Parameter","created":"2022-09-15","cited_by_count":3,"area":null},{"id":"2302.07975","title":"Multi-Task Differential Privacy Under Distribution Skew","created":"2023-02-15","cited_by_count":3,"area":null},{"id":"2407.12396","title":"Private and Federated Stochastic Convex Optimization: Efficient Strategies for Centralized Systems","created":"2024-07-17","cited_by_count":3,"area":null},{"id":"2206.05942","title":"Private Synthetic Data with Hierarchical Structure","created":"2022-06-13","cited_by_count":2,"area":null},{"id":"2406.04868","title":"Perturb-and-Project: Differentially Private Similarities and Marginals","created":"2024-06-07","cited_by_count":1,"area":null},{"id":"2406.19040","title":"On Convex Optimization with Semi-Sensitive Features","created":"2024-06-27","cited_by_count":1,"area":null},{"id":"2501.03222","title":"Characterizing the Accuracy-Communication-Privacy Trade-off in Distributed Stochastic Convex Optimization","created":"2025-01-06","cited_by_count":1,"area":null},{"id":"2506.02563","title":"Privacy-Preserving Federated Convex Optimization: Balancing Partial-Participation and Efficiency via Noise Cancellation","created":"2025-06-03","cited_by_count":1,"area":null},{"id":"2303.04195","title":"PRIMO: Private Regression in Multiple Outcomes","created":"2023-03-07","cited_by_count":0,"area":null},{"id":"2602.01607","title":"Minimax optimal differentially private synthetic data for smooth queries","created":"2026-02-02","cited_by_count":0,"area":null},{"id":"2602.07732","title":"Efficient Adaptive Data Analysis over Dense Distributions","created":"2026-02-07","cited_by_count":0,"area":null}],"next_cursor":null}