Latest Articles for Data Privacy

Methods to estimate dataset characteristics while keeping individual data safe.

New method improves federated learning while protecting user privacy.

Increasing communication rounds reduces costs and improves model performance in federated learning.

A new approach to improve user-specific experiences in language models.

A look into privacy methods and their effectiveness in data sharing.

A new method enhances privacy protection while training deep learning models.

A look into new methods for ad measurement that prioritize user privacy.

This article addresses how to simulate client data for faster federated learning.

New methods in Federated Learning enhance privacy and model performance while handling diverse data.

Explore the privacy challenges posed by inference attacks in machine learning models.

A new framework enhances prediction accuracy and data privacy in federated learning.

Introducing new methods to improve forgetting processes in contrastive learning models.

New attack method raises concerns about privacy in document understanding models.

Exploring federated learning and unlearning for user privacy and model integrity.

Introducing a method to fine-tune LLMs on low-resource devices.

A study on improving federated learning models for devices with limited resources.

A new method sheds light on how language models remember training data.

A new method creates reliable prediction intervals using diverse data while ensuring privacy.

Learn about cookies, their risks, and how to protect your privacy.

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

New framework enables efficient learning of diseases without storing past data.

Quantum machine learning offers new ways to protect sensitive data.

A new framework improves recommendations while protecting user privacy.

A structured approach to responsible AI design and validation.

An analysis of how online services handle children's data privacy.

A breakthrough system allows fast LLM operations on smartphones, enhancing user privacy.

Exploring vulnerabilities in Personalized Federated Learning and emerging backdoor attack methods.

Discover how federated learning is transforming food research through data privacy and collaboration.

UGradSL offers a practical solution for removing sensitive information from machine learning models.

This article discusses the challenges of machine unlearning and a new approach to balance privacy and accuracy.

A new method enhances language model performance on personal devices while addressing privacy concerns.

Assessing the gap between AI technology and regulatory frameworks.

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

Discover how private quantum computing can protect sensitive data during complex calculations.

A look at regulations shaping AI's role in global healthcare today.

Examining the security risks and solutions for emerging AI assistant technologies.

A new method improves Large Language Models' ability to forget sensitive information.

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

A new algorithm improves federated learning efficiency while ensuring data privacy.

Exploring how structural causal information can improve synthetic data quality.