:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Ferrando, Cecilia, Sheldon, Daniel
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2405.15002
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Private Adaptive Covariance Estimation via Gaussian Graphical Models
by: Ferrando, Cecilia, et al.
Published: (2026)

Noise-Calibrated Inference from Differentially Private Sufficient Statistics in Exponential Families
by: Asiaee, Amir, et al.
Published: (2026)

Differentially Private Linear Regression and Synthetic Data Generation with Statistical Guarantees
by: Lin, Shurong, et al.
Published: (2025)

One-Shot Federated Ridge Regression: Exact Recovery via Sufficient Statistic Aggregation
by: Alsulaimawi, Zahir
Published: (2026)

Joint Selection: Adaptively Incorporating Public Information for Private Synthetic Data
by: Fuentes, Miguel, et al.
Published: (2024)

Generalized Data Thinning Using Sufficient Statistics
by: Dharamshi, Ameer, et al.
Published: (2023)

Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares
by: Brown, Gavin, et al.
Published: (2024)

A Statistical Theory of Contrastive Learning via Approximate Sufficient Statistics
by: Lin, Licong, et al.
Published: (2025)

Efficient and Private Marginal Reconstruction with Local Non-Negativity
by: Mullins, Brett, et al.
Published: (2024)

High-Dimensional Differentially Private Quantile Regression: Distributed Estimation and Statistical Inference
by: Shen, Ziliang, et al.
Published: (2025)

Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation
by: Chen, Xuexin, et al.
Published: (2024)

Beyond Covariance Matrix: The Statistical Complexity of Private Linear Regression
by: Chen, Fan, et al.
Published: (2025)

Exploring the Impact of Dataset Statistical Effect Size on Model Performance and Data Sample Size Sufficiency
by: Hatamian, Arya, et al.
Published: (2025)

Private Sketches for Linear Regression
by: Das, Shrutimoy, et al.
Published: (2025)

Differentially Private Geodesic Regression
by: Kulkarni, Aditya, et al.
Published: (2025)

Statistical Robustness of Interval CVaR Based Regression Models under Perturbation and Contamination
by: You, Yulei, et al.
Published: (2026)

Private Statistical Estimation via Truncation
by: Zampetakis, Manolis, et al.
Published: (2025)

Asymptotics of Linear Regression with Linearly Dependent Data
by: Moniri, Behrad, et al.
Published: (2024)

Noise-Aware Differentially Private Regression via Meta-Learning
by: Räisä, Ossi, et al.
Published: (2024)

Autonomous Assessment of Demonstration Sufficiency via Bayesian Inverse Reinforcement Learning
by: Trinh, Tu, et al.
Published: (2022)

Toward Sufficient Statistical Power in Algorithmic Bias Assessment: A Test for ABROCA
by: Borchers, Conrad
Published: (2025)

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

Stabilizing Private LASSO under Heterogeneous Covariates via Anisotropic Objective Perturbation
by: Tanzawa, Haruka, et al.
Published: (2026)

PRIMO: Private Regression in Multiple Outcomes
by: Neel, Seth
Published: (2023)

Latent Noise Injection for Private and Statistically Aligned Synthetic Data Generation
by: Shen, Rex, et al.
Published: (2025)

Nearly Optimal Differentially Private ReLU Regression
by: Ding, Meng, et al.
Published: (2025)

High-Dimensional Private Linear Regression with Optimal Rates
by: Bombari, Simone, et al.
Published: (2025)

Optimal Bounds for Private Minimum Spanning Trees via Input Perturbation
by: Pagh, Rasmus, et al.
Published: (2024)

Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models
by: Lai, Jinlin, et al.
Published: (2024)

Beyond Statistical Estimation: Differentially Private Individual Computation via Shuffling
by: Wang, Shaowei, et al.
Published: (2024)

On The Statistical Representation Properties Of The Perturb-Softmax And The Perturb-Argmax Probability Distributions
by: Indelman, Hedda Cohen, et al.
Published: (2024)

Towards Robust Federated Analytics via Differentially Private Measurements of Statistical Heterogeneity
by: Scott, Mary, et al.
Published: (2024)

On Differentially Private U Statistics
by: Chaudhuri, Kamalika, et al.
Published: (2024)

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

Statistical Advantages of Perturbing Cosine Router in Mixture of Experts
by: Nguyen, Huy, et al.
Published: (2024)

PREM: Privately Answering Statistical Queries with Relative Error
by: Ghazi, Badih, et al.
Published: (2025)

$(ε, δ)$-Differentially Private Partial Least Squares Regression
by: Nikzad-Langerodi, Ramin, et al.
Published: (2024)

Refined Differentially Private Linear Regression via Extension of a Free Lunch Result
by: S, Sasmita Harini, et al.
Published: (2026)

Conditional Dependence via U-Statistics Pruning
by: de Cabrera, Ferran, et al.
Published: (2024)

Private Linear Regression with Differential Privacy and PAC Privacy
by: Yang, Hillary, et al.
Published: (2024)