Differential privacy and robust statistics

No abstract is available for this paper.

• Publication year

  2009

• Venue

  Symposium on the Theory of Computing

• Publication date

  2009-05-31

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.1145/1536414.1536466
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• A learning theory approach to non-interactive database privacy

  2008cited by this paper
• Efficient, Differentially Private Point Estimators

  2008cited by this paper
• What Can We Learn Privately?

  2008cited by this paper
• Privacy, accuracy, and consistency too: a holistic solution to contingency table release

  2007cited by this paper
• An Ad Omnia Approach to Defining and Achieving Private Data Analysis

  2007cited by this paper
• Smooth sensitivity and sampling in private data analysis

  2007cited by this paper
• Pseudorandom Bits for Polynomials

  2007cited by this paper
• Our Data, Ourselves: Privacy Via Distributed Noise Generation

  2006cited by this paper
• Differential Privacy

  2006cited by this paper
• Calibrating Noise to Sensitivity in Private Data Analysis

  2006cited by this paper
• Practical privacy: the SuLQ framework

  2005cited by this paper
• THE “JACKKNIFE” METHOD: CONFIDENTIALITY PROTECTION FOR COMPLEX STATISTICAL ANALYSES

  2005cited by this paper
• Privacy-Preserving Datamining on Vertically Partitioned Databases

  2004cited by this paper
• Convex Analysis And Nonlinear Optimization

  2000cited by this paper
• Robust Statistics: The Approach Based on Influence Functions

  1987cited by this paper
• On the histogram as a density estimator:L2 theory

  1981cited by this paper
• ON CONVERGENCE OF STOCHASTIC PROCESSES

  1962cited by this paper
• On the deviations of the empiric distribution function of vector chance variables

  1958cited by this paper
• On the Mathematical Foundations of Theoretical Statistics

  year unknowncited by this paper

• Differentially Private Retrieval-Augmented Generation

  2026cites this paper
• Towards Provably Unbiased LLM Judges via Bias-Bounded Evaluation

  2026cites this paper
• Less Noise, Same Certificate: Retain Sensitivity for Unlearning

  2026cites this paper
• Dependent Coeffects for Local Sensitivity Analysis

  2026cites this paper
• On the power of private likelihood-ratio tests for goodness-of-fit in frequency tables

  2026cites this paper
• From Statistical Disclosure Control to Fair AI: Navigating Fundamental Tradeoffs in Differential Privacy

  2026cites this paper
• Differentially Private Multimodal In-Context Learning

  2026cites this paper
• Differentially Private Two-Stage Empirical Risk Minimization and Applications to Individualized Treatment Rule

  2026cites this paper
• Location Privacy-Aware High-Altitude Platforms Data Collection and Trajectory Optimization

  2026cites this paper
• Noise Reduction for Pufferfish Privacy: A Practical Noise Calibration Method

  2026cites this paper
• Robust and Differentially Private PCA for non-Gaussian data

  2025cites this paper
• Adapting to Linear Separable Subsets with Large-Margin in Differentially Private Learning

  2025cites this paper
• Practical and Accurate Local Edge Differentially Private Graph Algorithms

  2025cites this paper
• The Double-Edged Nature of the Rashomon Set for Trustworthy Machine Learning

  2025cites this paper
• An improved differential privacy-preserving technique for educational dataset

  2025cites this paper
• Robust Probabilistic Inference via a Constrained Transport Metric

  2025cites this paper
• Asymptotic Matrix-Variate Bingham Distributions and Privacy-Preserving Principal Component Analysis

  2025cites this paper
• Purifying Approximate Differential Privacy with Randomized Post-processing

  2025influential citation
• Differentially Private Distribution Estimation Using Functional Approximation

  2025cites this paper
• Synthetic data as external control arms in scarce single-arm clinical trials

  2025cites this paper
• DP-SGD-global-adapt-V2-S: Triad improvements of privacy, accuracy and fairness via step decay noise multiplier and step decay upper clipping threshold

  2025cites this paper
• Robust Relatable Explanations of Machine Learning with Disentangled Cue-specific Saliency

  2025cites this paper
• Access Denied: Meaningful Data Access for Quantitative Algorithm Audits

  2025cites this paper
• Improving Private Random Forest Prediction Using Matrix Representation

  2025cites this paper
• Differentially private ratio statistics

  2025cites this paper
• Wasserstein GAN for moving differential privacy protection

  2025cites this paper
• A differentially private GLM model selection

  2025cites this paper
• Differential Privacy Configurations in the Real World: A Comparative Analysis

  2025cites this paper
• Robust Estimation Under Heterogeneous Corruption Rates

  2025cites this paper
• Differentially Private Triangle Counting Assisted by $k$-Anonymity in Two-Party Models

  2025cites this paper
• Differentially private explanations for aggregate query answers

  2025cites this paper
• From Centralized to Decentralized Federated Learning: Theoretical Insights, Privacy Preservation, and Robustness Challenges

  2025cites this paper
• An $\tilde{O}$ptimal Differentially Private Learner for Concept Classes with VC Dimension 1

  2025cites this paper
• Differentially Private Learners for Heterogeneous Treatment Effects

  2025influential citation
• Robust and Differentially Private Principal Component Analysis

  2025cites this paper
• Reinforced Generation of Combinatorial Structures: Hardness of Approximation

  2025cites this paper
• Fully Dynamic Algorithms for Graph Databases with Edge Differential Privacy

  2025cites this paper
• Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyond

  2025cites this paper
• CropsDisNet: An AI-Based Platform for Disease Detection and Advancing On-Farm Privacy Solutions

  2025cites this paper
• Research on efficient data processing method for fog computing based on blockchain and federated learning

  2025cites this paper
• Privacy Risks of Federated Knowledge Graph Embedding: New Membership Inference Attacks and Personalized Differential Privacy Defense

  2025cites this paper
• Improved subsample-and-aggregate via the private modified winsorized mean

  2025cites this paper
• Tukey Depth Mechanisms for Practical Private Mean Estimation

  2025cites this paper
• Privately Evaluating Untrusted Black-Box Functions

  2025cites this paper
• Safeguarding Privacy in Real-Time Trajectory Releases for AI-Driven Consumer Applications

  2025cites this paper
• DPO-Face: Differential privacy obfuscation for facial sensitive regions

  2025cites this paper
• A General Framework for Per-record Differential Privacy

  2025cites this paper
• Event Concealment in Discrete Event With Observation Losses Systems via Differential Privacy

  2025cites this paper
• Secure Two-Party Frequent Itemset Mining With Guaranteeing Differential Privacy

  2025cites this paper
• Differentially Private and Scalable Estimation of the Network Principal Component

  2025influential citation
• Benchmarking Fraud Detectors on Private Graph Data

  2025cites this paper
• PrivATE: Differentially Private Confidence Intervals for Average Treatment Effects

  2025influential citation
• Reinforced Generation of Combinatorial Structures: Applications to Complexity Theory

  2025cites this paper
• FedGA-Tree: Federated Decision Tree using Genetic Algorithm

  2025cites this paper
• Differentially private testing for relevant dependencies in high dimensions

  2025influential citation
• Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models

  2025cites this paper
• Estimating Group Means Under Local Differential Privacy

  2025cites this paper
• Breaking the n1.5 Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander Decomposition

  2025influential citation
• Sub-region Differential Privacy Trajectory Data Publishing Method Based on Trajectory Segment Prefix Tree

  2025cites this paper
• Crypto-Assisted Graph Degree Sequence Release under Local Differential Privacy

  2025cites this paper
• Hiding in the Network: Attribute-Oriented Differential Privacy for Graph Neural Networks

  2025cites this paper
• High‐Performance Statistical Computing (HPSC): Challenges, Opportunities, and Future Directions

  2025cites this paper
• Unifying Laplace Mechanism with Instance Optimality in Differential Privacy

  2025cites this paper
• MDM-Privacy: A Derivative-Driven Framework for Differential Privacy

  2025cites this paper
• Enhancing Privacy Through Unlinkable Data Sharing with User-in-the-Loop Access Control

  2025cites this paper
• PRIMA: Privacy preserving Multi-dimensional Analytic Approach

  2025cites this paper
• Time-Aware Projections: Truly Node-Private Graph Statistics under Continual Observation*

  2024cites this paper
• Location Privacy-Aware Task Offloading in Mobile Edge Computing

  2024cites this paper
• Provable Privacy with Non-Private Pre-Processing

  2024cites this paper
• Private PAC Learning May be Harder than Online Learning

  2024cites this paper
• Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation

  2024cites this paper
• General inferential limits under differential and Pufferfish privacy

  2024cites this paper
• Privacy Profiles for Private Selection

  2024influential citation
• Distribution Learnability and Robustness

  2024cites this paper
• Privacy-preserving Quantile Treatment Effect Estimation for Randomized Controlled Trials

  2024cites this paper
• Bridging Privacy and Robustness for Trustworthy Machine Learning

  2024cites this paper
• Sublinear Space Graph Algorithms in the Continual Release Model

  2024cites this paper
• Differentially Private Iterative Screening Rules for Linear Regression

  2024cites this paper
• Differentially Private Equivalence Testing for Continuous Distributions and Applications

  2024cites this paper
• Personalized Truncation for Personalized Privacy

  2024cites this paper
• SoS Certificates for Sparse Singular Values and Their Applications: Robust Statistics, Subspace Distortion, and More

  2024cites this paper
• StreamDP: Continual Observation of Real-world Data Streams with Differential Privacy

  2024cites this paper
• The Broader Landscape of Robustness in Algorithmic Statistics

  2024cites this paper
• Private Linear Regression with Differential Privacy and PAC Privacy

  2024cites this paper
• Differentially Private Multi-Sampling from Distributions

  2024cites this paper
• Adaptive Privacy for Differentially Private Causal Graph Discovery

  2024cites this paper
• Dimension-free Private Mean Estimation for Anisotropic Distributions

  2024cites this paper
• Density clustering-based optimization model for trajectory data publication

  2024influential citation
• Differentially Private Substring and Document Counting

  2024cites this paper
• VPPFL: Verifiable Privacy-Preserving Federated Learning in Cloud Environment

  2024cites this paper
• CURATE: Scaling-Up Differentially Private Causal Graph Discovery

  2024cites this paper
• Enhancing Privacy in Recommender Systems through Differential Privacy Techniques

  2024cites this paper
• Trajectory-aware privacy-preserving method with local differential privacy in crowdsourcing

  2024cites this paper
• Fully Dynamic Graph Algorithms with Edge Differential Privacy

  2024cites this paper
• Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning

  2024cites this paper
• Better Gaussian Mechanism using Correlated Noise

  2024cites this paper
• The Complexities of Differential Privacy for Survey Data

  2024cites this paper
• Utilitarian Privacy and Private Sampling

  2024cites this paper
• BTMDS: Blockchain trusted medical data sharing scheme with privacy protection and access control

  2024cites this paper
• Anonymization: The imperfect science of using data while preserving privacy

  2024cites this paper