{"total":40,"rows":[{"id":"2303.00654","title":"How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy","created":"2023-03-01","cited_by_count":153,"area":null},{"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":"2103.06641","title":"Differentially Private Query Release Through Adaptive Projection","created":"2021-03-11","cited_by_count":52,"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":"2209.07400","title":"Private Synthetic Data for Multitask Learning and Marginal Queries","created":"2022-09-15","cited_by_count":35,"area":null},{"id":"2211.04446","title":"Private Set Generation with Discriminative Information","created":"2022-11-07","cited_by_count":34,"area":null},{"id":"2306.03257","title":"Generating Private Synthetic Data with Genetic Algorithms","created":"2023-06-05","cited_by_count":18,"area":null},{"id":"2305.10994","title":"Graphical vs. Deep Generative Models: Measuring the Impact of Differentially Private Mechanisms and Budgets on Utility","created":"2023-05-18","cited_by_count":13,"area":null},{"id":"2406.13985","title":"The Elusive Pursuit of Reproducing PATE-GAN: Benchmarking, Auditing, Debugging","created":"2024-06-20","cited_by_count":13,"area":null},{"id":"2207.05810","title":"dpart: Differentially Private Autoregressive Tabular, a General Framework for Synthetic Data Generation","created":"2022-07-12","cited_by_count":12,"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":"2305.15538","title":"Post-processing Private Synthetic Data for Improving Utility on Selected Measures","created":"2023-05-24","cited_by_count":9,"area":null},{"id":"2306.15056","title":"Optimal Differentially Private Model Training with Public Data","created":"2023-06-26","cited_by_count":9,"area":null},{"id":"2401.17823","title":"Privacy-preserving data release leveraging optimal transport and particle gradient descent","created":"2024-01-31","cited_by_count":8,"area":null},{"id":"2403.07797","title":"Joint Selection: Adaptively Incorporating Public Information for Private Synthetic Data","created":"2024-03-12","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":"2402.09483","title":"Oracle-Efficient Differentially Private Learning with Public Data","created":"2024-02-13","cited_by_count":6,"area":null},{"id":"2411.03351","title":"Tabular Data Synthesis with Differential Privacy: A Survey","created":"2024-11-04","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":"2309.15696","title":"A Unified View of Differentially Private Deep Generative Modeling","created":"2023-09-27","cited_by_count":4,"area":null},{"id":"2312.11712","title":"A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy","created":"2023-12-18","cited_by_count":4,"area":null},{"id":"2401.08089","title":"A Study on Training and Developing Large Language Models for Behavior Tree Generation","created":"2024-01-16","cited_by_count":4,"area":null},{"id":"2405.15002","title":"Private Regression via Data-Dependent Sufficient Statistic Perturbation","created":"2024-05-23","cited_by_count":4,"area":null},{"id":"2506.00322","title":"dpmm: Differentially Private Marginal Models, a Library for Synthetic Tabular Data Generation","created":"2025-05-31","cited_by_count":3,"area":null},{"id":"2104.01987","title":"Rejoinder: Gaussian Differential Privacy","created":"2021-04-05","cited_by_count":2,"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":"2305.08175","title":"ResidualPlanner+: a scalable matrix mechanism for marginals and beyond","created":"2023-05-14","cited_by_count":2,"area":null},{"id":"2405.18670","title":"Differentially Private Synthetic Data Generation for Relational Databases","created":"2024-05-29","cited_by_count":2,"area":null},{"id":"2410.19941","title":"Privacy without Noisy Gradients: Slicing Mechanism for Generative Model Training","created":"2024-10-25","cited_by_count":2,"area":null},{"id":"2303.11079","title":"Differentially Private Algorithms for Synthetic Power System Datasets","created":"2023-03-20","cited_by_count":1,"area":null},{"id":"2310.09729","title":"Private Synthetic Data Meets Ensemble Learning","created":"2023-10-15","cited_by_count":1,"area":null},{"id":"2601.22434","title":"Rethinking Anonymity Claims in Synthetic Data Generation: A Model-Centric Privacy Attack Perspective","created":"2026-01-30","cited_by_count":1,"area":null},{"id":"2304.01108","title":"Coincidental Generation","created":"2023-04-03","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":"2509.07018","title":"Private Queries with Sigma-Counting","created":"2025-09-07","cited_by_count":0,"area":null},{"id":"2511.13893","title":"Beyond One-Size-Fits-All: Neural Networks for Differentially Private Tabular Data Synthesis","created":"2025-11-17","cited_by_count":0,"area":null},{"id":"2606.11283","title":"Fixed-Parameter Tractability of Private Synthetic Data Generation","created":"2026-06-09","cited_by_count":0,"area":null},{"id":"2609.00708","title":"Differentially Private Paired Table-Image Multimodal Synthesis","created":"2026-09-01","cited_by_count":0,"area":null}],"next_cursor":null}