Differential Privacy

  1. Differential Privacy in Practice
    1. Basic Statistical Queries
      1. Counting Queries
        1. Mechanism Selection
          1. Accuracy Considerations
            1. Confidence Intervals
            2. Histograms
              1. Binning Strategies
                1. Noise Calibration
                  1. Consistency Constraints
                    1. Hierarchical Histograms
                    2. Sums and Averages
                      1. Sensitivity Analysis
                        1. Mechanism Selection
                          1. Bounded vs Unbounded Domains
                          2. Medians and Quantiles
                            1. Challenges in Sensitivity
                              1. Exponential Mechanism Approach
                                1. Smooth Sensitivity Approach
                                2. Range Queries
                                  1. Multi-dimensional Histograms
                                    1. Wavelet-based Methods
                                      1. Matrix Mechanism
                                    2. Advanced Query Processing
                                      1. Continual Observation
                                        1. Binary Tree Mechanism
                                          1. Honaker's Method
                                            1. Event-Level Privacy
                                            2. Interactive Query Processing
                                              1. Query Optimization
                                                1. Privacy Budget Management
                                                  1. Adaptive Strategies
                                                  2. Complex Analytical Queries
                                                    1. Join Operations
                                                      1. Group-by Aggregations
                                                        1. Subquery Processing
                                                      2. Differentially Private Synthetic Data Generation
                                                        1. Motivation and Applications
                                                          1. Methods for Synthetic Data
                                                            1. PrivBayes
                                                              1. Bayesian Network Learning
                                                                1. Noisy Conditional Distributions
                                                                  1. Strengths and Limitations
                                                                  2. DP-GANs
                                                                    1. Generative Adversarial Networks
                                                                      1. DP-SGD for Training
                                                                        1. Mode Collapse Issues
                                                                          1. Strengths and Limitations
                                                                          2. Marginal-based Methods
                                                                            1. MWEM Algorithm
                                                                              1. Multiplicative Weights
                                                                                1. High-dimensional Challenges
                                                                              2. Evaluation Metrics
                                                                                1. Utility Measures
                                                                                  1. Privacy Auditing
                                                                                    1. Statistical Tests
                                                                                  2. Differential Privacy in Machine Learning
                                                                                    1. Differentially Private Training
                                                                                      1. DP-SGD Algorithm
                                                                                        1. Gradient Clipping
                                                                                          1. Noise Addition
                                                                                            1. Privacy Accounting
                                                                                              1. Hyperparameter Tuning
                                                                                              2. Impact on Model Accuracy
                                                                                                1. Convergence Analysis
                                                                                                2. Private Aggregation of Teacher Ensembles
                                                                                                  1. Protocol Overview
                                                                                                    1. Teacher Model Training
                                                                                                      1. Student Model Distillation
                                                                                                        1. Use Cases and Limitations
                                                                                                        2. Output vs Objective Perturbation
                                                                                                          1. Definitions and Differences
                                                                                                            1. Use Cases and Trade-offs
                                                                                                              1. Stability Analysis
                                                                                                              2. Private Feature Selection
                                                                                                                1. Stability-based Methods
                                                                                                                  1. Exponential Mechanism Approach
                                                                                                                  2. Private Model Selection
                                                                                                                    1. Cross-validation with DP
                                                                                                                      1. Hyperparameter Optimization
                                                                                                                        1. Model Comparison

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                                                                                                                    5. Models of Differential Privacy Deployment

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                                                                                                                    7. Advanced Topics and Current Research