Latest Articles for Differential Privacy

A new method combines explainability with privacy in clustering for better data insights.

A study on preserving privacy while analyzing sensitive data using differential privacy techniques.

New algorithms improve privacy and accuracy in geometric median calculations.

A method combining SGD and privacy techniques for effective data analysis.

A study on methods for safe synthetic data that maintains privacy and usefulness.

Examining how algorithms can protect privacy while optimizing decisions in personalized medicine.

A new framework for analyzing data streams while ensuring user privacy.

Analyzing data privacy through Bayesian inference with constraints.

Addressing overfitting and privacy issues in evolving datasets.

This article discusses a new method to improve robustness against adversarial attacks in image classification.

Blending traditional clustering methods with privacy protections using differential privacy.

A method to maintain privacy while sharing urban traffic statistics.

LDMeta enhances privacy and efficiency in distributed learning methods.

This article explores how differential privacy safeguards ECG data in healthcare.

This article explores strategies for protecting individual privacy in machine learning.

A new method for estimating edge density in random graphs while ensuring privacy.

Exploring privacy-preserving technologies in medical image analysis.

Exploring techniques for privacy-preserving data analysis while ensuring accuracy.

This work enhances privacy in graph diffusion while maintaining data utility.

Learn how differential privacy protects individual data while allowing useful analysis.

Lomas enables secure access to public data for research without compromising privacy.

This article presents a method to protect personal data in machine learning systems.

New methods reveal serious privacy threats from location data sharing.

New methods generate synthetic data to protect privacy in collaborative scenarios.

A new approach to boxplots ensures data privacy while maintaining insightful analysis.

This article discusses creating reliable hypothesis tests despite data corruption.

Examining the relationship between privacy techniques and biases in language models.

New methods improve privacy and coherence using collocations in language data.

A new method for rewriting text that ensures privacy and maintains meaning.

This study assesses advanced models for generating fake trip data and their practical applications.

A method for estimating community memberships while protecting individual privacy.

Cities gain crucial transport data while addressing privacy concerns.

Examining differential privacy's effectiveness in protecting individual identities in SOEP data.

Creating systems that promote truthfulness among users in various digital interactions.

This research discusses federated learning's role in protecting privacy during data analysis.

New methods for statistical testing while protecting data privacy through federated learning.

Exploring challenges and advancements in protecting sensitive data while maintaining its usefulness.

Data-driven techniques must protect privacy while identifying the best options.

The challenge of combining differential privacy with sublinear algorithms in data analysis.

A look at federated learning combining differential privacy and blockchain for data security.