Latest Articles for Differential Privacy

Examining generative models for synthetic gene expression data while ensuring patient privacy.

Exploring how Differential Privacy protects personal data while providing valuable insights.

New methods enhance privacy in machine learning by refining private selection mechanisms.

Examining the relationship between data protection laws and machine learning practices.

A new audio-based method estimates crowd sizes without invading personal privacy.

A method for conducting Bayesian tests while safeguarding individual privacy.

Exploring methods to safeguard individual data in an information-driven world.

A look at how random walk algorithms improve privacy in decentralized learning.

This article covers methods to estimate bus speeds while protecting privacy.

Combining Federated Learning with privacy techniques protects sensitive data while training models.

Exploring the balance between privacy and learning efficiency in machine learning.

Researchers find ways to safeguard sensitive data in cooperative agent environments.

A look into reconstruction attacks and their impact on data privacy in machine learning.

New methods enhance privacy and accuracy in secure computing environments.

Addressing privacy concerns in systems that manage sensitive data.

Addressing privacy concerns in machine learning with effective techniques.

Addressing the challenge of privacy in data-driven decision-making for healthcare.

Exploring how larger batch sizes improve differential privacy in machine learning.

Examining the challenges of differential privacy in online learning systems.

Exploring local differential privacy methods for secure graph analysis.

Exploring differential privacy methods in reinforcement learning to protect sensitive data.

Discussing privacy and fairness in machine learning through differential privacy and worst-group risk.

New algorithms enhance privacy and accuracy in sparse data scenarios.

A look at how data analysis can maintain individual privacy.

Examining privacy dangers in Federated Learning and large language models.

A novel method enhances energy load predictions while ensuring data privacy.

A new approach improves machine learning accuracy while ensuring data privacy.

A new approach to image representation with differential privacy through captioning.

Exploring methods for secure information sharing in group discussions.

This article discusses privacy solutions for Max Cover and Set Cover problems.

New mechanisms enhance privacy while preserving data utility in machine learning.

Innovative algorithms use public data to protect privacy in data analysis.

This research reveals privacy threats in simpler topic models like LDA.

This article discusses privacy methods for tabular data in large language models.

Exploring recent insights on synthetic data and privacy challenges.

A new mechanism enhances synthetic data generation while protecting individual privacy.

Examining the impact of data priors on differential privacy in image reconstruction attacks.

New methods aim to enhance data removal in language models while preserving performance.

A new method for secure localization without compromising sensitive data.

New methods safeguard personal data in image generation.