{"total":15,"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":"2302.03098","title":"One-shot Empirical Privacy Estimation for Federated Learning","created":"2023-02-06","cited_by_count":36,"area":null},{"id":"2308.10888","title":"Unlocking Accuracy and Fairness in Differentially Private Image Classification","created":"2023-08-21","cited_by_count":16,"area":null},{"id":"2307.03928","title":"Bounding data reconstruction attacks with the hypothesis testing interpretation of differential privacy","created":"2023-07-08","cited_by_count":15,"area":null},{"id":"2507.06969","title":"Unifying Re-Identification, Attribute Inference, and Data Reconstruction Risks in Differential Privacy","created":"2025-07-09","cited_by_count":15,"area":null},{"id":"2312.05114","title":"The Inadequacy of Similarity-based Privacy Metrics: Privacy Attacks against \"Truly Anonymous\" Synthetic Datasets","created":"2023-12-08","cited_by_count":14,"area":null},{"id":"2305.04146","title":"Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information","created":"2023-05-06","cited_by_count":13,"area":null},{"id":"2306.03235","title":"Information Flow Control in Machine Learning through Modular Model Architecture","created":"2023-06-05","cited_by_count":11,"area":null},{"id":"2310.20579","title":"Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks","created":"2023-10-31","cited_by_count":10,"area":null},{"id":"2403.02506","title":"Differentially Private Representation Learning via Image Captioning","created":"2024-03-04","cited_by_count":5,"area":null},{"id":"2408.16913","title":"Analyzing Inference Privacy Risks Through Gradients in Machine Learning","created":"2024-08-29","cited_by_count":4,"area":null},{"id":"2402.08344","title":"Implicit Bias in Noisy-SGD: With Applications to Differentially Private Training","created":"2024-02-13","cited_by_count":2,"area":null},{"id":"2510.07304","title":"Cocoon: A System Architecture for Differentially Private Training with Correlated Noises","created":"2025-10-08","cited_by_count":1,"area":null},{"id":"2609.37344","title":"A Sharp Transition in Data Reconstruction under Differential Privacy","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.13768","title":"From Pixels to Privacy-Sensitive Features: An Information-Theoretic Framework for Reconstruction Bounds","created":"2026-10-09","cited_by_count":0,"area":null}],"next_cursor":null}