Tales of Obfuscation in Bounded Arithmetic, Metacomplexity, and Differential Privacy
Explores obfuscation's role in theoretical computer science, covering Circuit Range Avoidance, metacomplexity of Kolmogorov complexity, and computational differential privacy, with focus on recent results and open questions.
Implementing Differential Privacy for the 2020 US Census
Explore the implementation of differential privacy for the 2020 US Census, including technical challenges, organizational hurdles, and the development of innovative algorithms to protect respondent privacy.
Platform Data Privacy and Security Strategies for Public Interest Research
Exploring technical strategies for data sharing in public interest research while complying with privacy regulations, addressing challenges and proposing industry standards.
Cynthia Dwork: The Mathematics of Privacy
Explore the mathematics of privacy with Cynthia Dwork, covering differential privacy, data analysis techniques, and advanced concepts in privacy-preserving algorithms.
Private Learning of Gaussians and Their Mixtures
Explore private learning techniques for Gaussian distributions and mixtures, focusing on robust methods, hypothesis selection, and high-dimensional cases.
Control, Confidentiality, and the Right to Be Forgotten
Explore legal and technical aspects of data erasure, focusing on machine unlearning, confidentiality, and adaptive history independence in differential privacy contexts.
Misspecification, and Uncertainty Quantification in Differential Privacy
Explore differential privacy's theoretical guarantees, misspecification issues, and uncertainty quantification methods. Gain insights into designing mechanisms and addressing implementation challenges.
MVG Mechanism - Differential Privacy under Matrix-Valued Query
Explore a novel differential privacy mechanism for matrix-valued queries, addressing challenges in data protection and improving upon existing methods.
CALM - Consistent Adaptive Local Marginal for Marginal Release under Local Differential Privacy
Explore constructing marginal tables with Local Differential Privacy, ensuring individual data protection without third-party reliance. Learn CALM protocol for consistent, adaptive local marginal release.
Privacy and Fairness
Explore differential privacy, stochastic optimization, and fairness in algorithms. Learn about new techniques, applications, and the importance of interaction in privacy-preserving machine learning.
Privacy-Preserving AI - Andrew Trask, University of Oxford
Explore privacy-preserving AI techniques with Andrew Trask, covering differential privacy, federated learning, and shared governance for ethical and secure AI development.
Recent Development in Differential Privacy I
Explore recent advancements in differential privacy, covering statistical queries, compressible estimators, and multiple comparisons in adaptive data analysis.
The Ethical Algorithm
Explore ethical challenges in algorithmic design, focusing on data privacy and fairness. Learn about differential privacy, anonymization techniques, and defining fairness in AI systems.
Individual Statistical Fairness
Explore statistical fairness in machine learning, focusing on individual-level impacts and false negative rates beyond differential privacy.
Privacy Amplification by Sampling and Renyi Differential Privacy
Explore privacy amplification, Renyi differential privacy, and sampling techniques in data analysis. Learn about SGD, use cases, and technical results for enhancing privacy in various applications.
Generative Adversarial Models for Privacy and Fairness
Explore generative adversarial models for enhancing privacy and fairness in machine learning, covering differential privacy, GANs, and real-world applications in data publishing and encoding.
Foundations and Applications of Data Privacy - A Perspective
Explore data privacy foundations, challenges, and applications, focusing on differential privacy concepts and their real-world implementations in tech and government sectors.
The Strange Case of Privacy in Equilibrium Models
Explores counterintuitive effects of privacy in targeted advertising, revealing how increased privacy can paradoxically lead to more information disclosure and unexpected economic outcomes.
Optimal and Differentially Private Data Acquisition: Central and Local Mechanisms
Explore central and local mechanisms for optimal and differentially private data acquisition, focusing on theoretical foundations and practical applications in statistical analysis.
Differentially Private Simple Linear Regression
Explore advanced techniques for protecting data privacy in statistical analysis, focusing on simple linear regression methods and their applications.
On the Complexity of Two-Party Differential Privacy
Explore the intricacies of two-party differential privacy, examining its complexity and implications for data analysis and privacy protection in collaborative settings.