Cover Image

Differentially Private Algorithms for Linear Queries via Stochastic Convex Optimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Micali, Giorgio, Lezane, Clement, Betken, Annika
Format:	Preprint
Published:	2024
Subjects:	Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Central limit theorems for the outputs of fully convolutional neural networks with time series input
by: Betken, Annika, et al.
Published: (2026)

A two-sample test based on averaged Wilcoxon rank sums over interpoint distances
by: Betken, Annika, et al.
Published: (2024)

Symmetry Testing in Time Series using Ordinal Patterns: A U-Statistic Approach
by: Betken, Annika, et al.
Published: (2026)

Ordinal Patterns Based Change Points Detection
by: Betken, Annika, et al.
Published: (2025)

Oblivious Stochastic Composite Optimization
by: Lezane, Clément, et al.
Published: (2023)

Enhancing Differentially Private Linear Regression via Public Second-Moment
by: Cao, Zilong, et al.
Published: (2025)

Differentially Private Range Queries with Correlated Input Perturbation
by: Dharangutte, Prathamesh, et al.
Published: (2024)

Statistical Inference for Differentially Private Stochastic Gradient Descent
by: Xia, Xintao, et al.
Published: (2025)

Differentially Private One-Shot Federated Inference for Linear Mixed Models via Lossless Likelihood Reconstruction
by: Hanada, Keisuke, et al.
Published: (2026)

Ordinal Patterns Based Testing of Spatial Independence in Irregular Spatial Structures
by: Micali, Giorgio, et al.
Published: (2026)

Optimal Algorithms for Stochastic Complementary Composite Minimization
by: d'Aspremont, Alexandre, et al.
Published: (2022)

Differentially Private Inference for Longitudinal Linear Regression
by: Sopa, Getoar, et al.
Published: (2026)

Differentially Private Methods for Compositional Data
by: Guo, Qi, et al.
Published: (2022)

Statistical Limits and Efficient Algorithms for Differentially Private Federated Learning
by: Auddy, Arnab, et al.
Published: (2026)

Differentially Private Boxplots
by: Ramsay, Kelly, et al.
Published: (2024)

Differentially Private Bayesian Inference for Gaussian Copula Correlations
by: Wang, Shuo, et al.
Published: (2026)

Versatile Differentially Private Learning for General Loss Functions
by: Lu, Qilong, et al.
Published: (2025)

Differentially Private Computation of the Gini Index for Income Inequality
by: Lan, Wenjie, et al.
Published: (2025)

Differentially Private Finite Population Estimation via Survey Weight Regularization
by: Seeman, Jeremy, et al.
Published: (2024)

A Bayesian Nonparametric Stochastic Block Model for Directed Acyclic Graphs
by: Lee, Clement, et al.
Published: (2023)

Logistic Regression Model for Differentially-Private Matrix Masked Data
by: Nghiem, Linh H, et al.
Published: (2024)

Differentially Private Multivariate Statistics with an Application to Contingency Table Analysis
by: Kim, Minwoo, et al.
Published: (2022)

Differentially Private Linear Regression with Linked Data
by: Lin, Shurong, et al.
Published: (2023)

Privacy-Preserving Cohort Analytics for Personalized Health Platforms: A Differentially Private Framework with Stochastic Risk Modeling
by: Chakraborty, Richik, et al.
Published: (2026)

Bayesian Methods to Improve The Accuracy of Differentially Private Measurements of Constrained Parameters
by: Janicki, Ryan, et al.
Published: (2024)

Differentially Private Estimation of Weighted Average Treatment Effects for Binary Outcomes
by: Guha, Sharmistha, et al.
Published: (2024)

Differentially Private Verification of Survey-Weighted Estimates
by: Lin, Tong, et al.
Published: (2024)

Differentially Private Conformal Prediction via Quantile Binary Search
by: Romanus, Ogonnaya M., et al.
Published: (2025)

Differentially Private E-Values
by: Csillag, Daniel, et al.
Published: (2025)

Optimal Differentially Private Randomized Response Designs to Collect Sensitive Binary Data
by: Karmakar, Bittu, et al.
Published: (2025)

Gaussian Differentially Private $e$-values: Construction, Threshold Calibration, and Multiple Testing
by: Kuang, Qi, et al.
Published: (2026)

Robust and Differentially Private PCA for non-Gaussian data
by: Kim, Minwoo, et al.
Published: (2025)

Ergodic Network Stochastic Differential Equations
by: Iafrate, Francesco, et al.
Published: (2024)

Bridging Constraints and Stochasticity: A Fully First-Order Method for Stochastic Bilevel Optimization with Linear Constraints
by: Phan, Cac, et al.
Published: (2025)

Fiducial Matching: Differentially Private Inference for Categorical Data
by: Romanus, Ogonnaya Michael, et al.
Published: (2025)

Convex Mixed-Integer Programming for Causal Additive Models with Optimization and Statistical Guarantees
by: Zhang, Xiaozhu, et al.
Published: (2025)

Differentially Private Covariate Balancing Causal Inference
by: Ohnishi, Yuki, et al.
Published: (2024)

Dynamic Modeling of Sparse Longitudinal Data and Functional Snippets With Stochastic Differential Equations
by: Zhou, Yidong, et al.
Published: (2023)

Robust Parameter Estimation in Dynamical Systems by Stochastic Differential Equations
by: Sun, Qingchuan, et al.
Published: (2025)

Optimal Differentially Private Ranking from Pairwise Comparisons
by: Cai, T. Tony, et al.
Published: (2025)