The authors give an efficient non-interactive L-LDP algorithm for SCO achieving excess risk O(sqrt(K/(ε n))) in high privacy and O(sqrt(K/(e^ε n))) in medium privacy, with matching information-theoretic lower bounds for large n.
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response , year =
8 Pith papers cite this work. Polarity classification is still indexing.
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representative citing papers
Trade-off functions between two distributions are finitely testable if and only if their Neyman-Pearson rejection regions are attainable by a VC-class of sets.
ICLab is a new internet censorship measurement platform using commercial VPNs for global longitudinal detection of DNS manipulation, TCP injection, and block pages, with observations of 3,602 blocked URLs across 60 countries from 2017-2018 data.
Shuffled DP-SGD requires σ ≥ 1/√(2 ln M) or κ ≥ (1/√8)(1 - 1/√(4π ln M)) to limit adversarial advantage, preventing strong privacy and high utility simultaneously.
Proposes a formal DP-compatible framework with three unfairness measures (mutual information with TV proxy, MaxSAT-based repair, top-k tuple contribution) that satisfy positivity, monotonicity, and computability.
CPPDD is a new consensus-based protocol for privacy-preserving multi-client data sharing that achieves unanimous-release confidentiality, linear scalability, and high-probability malicious deviation detection.
LLMs achieve strong performance on website classification tasks relevant to web measurements and support a practical two-step methodology for targeted studies from the Tranco list.
The authors provide a systematization of differentially private graph release methods along with an objective-based framework and two illustrative evaluations for social network analysts.
citing papers explorer
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Convex Optimization with Local Label Differential Privacy: Tight Bounds in All Privacy Regimes
The authors give an efficient non-interactive L-LDP algorithm for SCO achieving excess risk O(sqrt(K/(ε n))) in high privacy and O(sqrt(K/(e^ε n))) in medium privacy, with matching information-theoretic lower bounds for large n.
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When Are Trade-Off Functions Testable from Finite Samples?
Trade-off functions between two distributions are finitely testable if and only if their Neyman-Pearson rejection regions are attainable by a VC-class of sets.
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ICLab: A Global, Longitudinal Internet Censorship Measurement Platform
ICLab is a new internet censorship measurement platform using commercial VPNs for global longitudinal detection of DNS manipulation, TCP injection, and block pages, with observations of 3,602 blocked URLs across 60 countries from 2017-2018 data.
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Fundamental Limitations of Favorable Privacy-Utility Guarantees for DP-SGD
Shuffled DP-SGD requires σ ≥ 1/√(2 ln M) or κ ≥ (1/√8)(1 - 1/√(4π ln M)) to limit adversarial advantage, preventing strong privacy and high utility simultaneously.
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Measuring Database Unfairness via Dependency Quantification Under Differential Privacy
Proposes a formal DP-compatible framework with three unfairness measures (mutual information with TV proxy, MaxSAT-based repair, top-k tuple contribution) that satisfy positivity, monotonicity, and computability.
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Secure, Verifiable, and Scalable Multi-Client Data Sharing via Consensus-Based Privacy-Preserving Data Distribution
CPPDD is a new consensus-based protocol for privacy-preserving multi-client data sharing that achieves unanimous-release confidentiality, linear scalability, and high-probability malicious deviation detection.
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LLM-Assisted Web Measurements
LLMs achieve strong performance on website classification tasks relevant to web measurements and support a practical two-step methodology for targeted studies from the Tranco list.
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SoK: Practical Aspects of Releasing Differentially Private Graphs
The authors provide a systematization of differentially private graph release methods along with an objective-based framework and two illustrative evaluations for social network analysts.