{"total":29,"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":"2202.08312","title":"Improved Differential Privacy for SGD via Optimal Private Linear Operators on Adaptive Streams","created":"2022-02-16","cited_by_count":59,"area":null},{"id":"2103.06641","title":"Differentially Private Query Release Through Adaptive Projection","created":"2021-03-11","cited_by_count":52,"area":null},{"id":"2306.08153","title":"(Amplified) Banded Matrix Factorization: A unified approach to private training","created":"2023-06-13","cited_by_count":49,"area":null},{"id":"2211.06530","title":"Multi-Epoch Matrix Factorization Mechanisms for Private Machine Learning","created":"2022-11-12","cited_by_count":48,"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":"2307.02106","title":"SoK: Privacy-Preserving Data Synthesis","created":"2023-07-05","cited_by_count":38,"area":null},{"id":"2302.01463","title":"Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy","created":"2023-02-02","cited_by_count":18,"area":null},{"id":"2306.03257","title":"Generating Private Synthetic Data with Genetic Algorithms","created":"2023-06-05","cited_by_count":18,"area":null},{"id":"2205.14485","title":"Noise-Aware Statistical Inference with Differentially Private Synthetic Data","created":"2022-05-28","cited_by_count":9,"area":null},{"id":"2208.07410","title":"Private Query Release via the Johnson-Lindenstrauss Transform","created":"2022-08-15","cited_by_count":8,"area":null},{"id":"2109.06153","title":"Relaxed Marginal Consistency for Differentially Private Query Answering","created":"2021-09-13","cited_by_count":6,"area":null},{"id":"2504.06923","title":"The Importance of Being Discrete: Measuring the Impact of Discretization in End-to-End Differentially Private Synthetic Data","created":"2025-04-09","cited_by_count":5,"area":null},{"id":"2402.08012","title":"Online Differentially Private Synthetic Data Generation","created":"2024-02-12","cited_by_count":4,"area":null},{"id":"2405.02341","title":"Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy","created":"2024-05-02","cited_by_count":4,"area":null},{"id":"2104.14808","title":"Improved Matrix Gaussian Mechanism for Differential Privacy","created":"2021-04-30","cited_by_count":3,"area":null},{"id":"2301.13850","title":"General Gaussian Noise Mechanisms and Their Optimality for Unbiased Mean Estimation","created":"2023-01-31","cited_by_count":3,"area":null},{"id":"2204.12903","title":"Spending Privacy Budget Fairly and Wisely","created":"2022-04-27","cited_by_count":2,"area":null},{"id":"2206.05942","title":"Private Synthetic Data with Hierarchical Structure","created":"2022-06-13","cited_by_count":2,"area":null},{"id":"2212.00135","title":"Answering Private Linear Queries Adaptively using the Common Mechanism","created":"2022-11-30","cited_by_count":2,"area":null},{"id":"2305.08175","title":"ResidualPlanner+: a scalable matrix mechanism for marginals and beyond","created":"2023-05-14","cited_by_count":2,"area":null},{"id":"2410.01091","title":"Efficient and Private Marginal Reconstruction with Local Non-Negativity","created":"2024-10-01","cited_by_count":1,"area":null},{"id":"2603.10099","title":"Denoising the US Census: Succinct Block Hierarchical Regression","created":"2026-03-10","cited_by_count":1,"area":null},{"id":"2604.00868","title":"Accurate and Scalable Matrix Mechanisms via Divide and Conquer","created":"2026-04-01","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":"2310.06371","title":"Partition-based differentially private synthetic data generation","created":"2023-10-10","cited_by_count":0,"area":null},{"id":"2402.07066","title":"Differentially Private Range Queries with Correlated Input Perturbation","created":"2024-02-10","cited_by_count":0,"area":null},{"id":"2408.16017","title":"Differentially Private Publication of Electricity Time Series Data in Smart Grids","created":"2024-08-24","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}],"next_cursor":null}