Cover Image

Scaling up the Banded Matrix Factorization Mechanism for Differentially Private ML

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	McKenna, Ryan
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Cryptography and Security Data Structures and Algorithms
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Normalized Square Root: Sharper Matrix Factorization Bounds for Differentially Private Continual Counting
by: Henzinger, Monika, et al.
Published: (2025)

Improved Accuracy for Private Continual Cardinality Estimation in Fully Dynamic Streams via Matrix Factorization
by: Andersson, Joel Daniel, et al.
Published: (2026)

Differentially Private Clustering in Data Streams
by: Epasto, Alessandro, et al.
Published: (2023)

Differentially Private Multi-Sampling from Distributions
by: Cheu, Albert, et al.
Published: (2024)

Differentially Private Learning Beyond the Classical Dimensionality Regime
by: Dwork, Cynthia, et al.
Published: (2024)

A Private Approximation of the 2nd-Moment Matrix of Any Subsamplable Input
by: Mahpud, Bar, et al.
Published: (2025)

A Differentially Private Clustering Algorithm for Well-Clustered Graphs
by: He, Weiqiang, et al.
Published: (2024)

On Differentially Private Subspace Estimation in a Distribution-Free Setting
by: Tsfadia, Eliad
Published: (2024)

Almost Tight Error Bounds on Differentially Private Continual Counting
by: Henzinger, Monika, et al.
Published: (2022)

Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent
by: Yu, Da, et al.
Published: (2022)

Differentially Private Bootstrap: New Privacy Analysis and Inference Strategies
by: Wang, Zhanyu, et al.
Published: (2022)

A Smooth Binary Mechanism for Efficient Private Continual Observation
by: Andersson, Joel Daniel, et al.
Published: (2023)

Differential Private Stochastic Optimization with Heavy-tailed Data: Towards Optimal Rates
by: Zhao, Puning, et al.
Published: (2024)

Making Old Things New: A Unified Algorithm for Differentially Private Clustering
by: la Tour, Max Dupré, et al.
Published: (2024)

A Polynomial Time, Pure Differentially Private Estimator for Binary Product Distributions
by: Singhal, Vikrant
Published: (2023)

Private Selection with Heterogeneous Sensitivities
by: Antonova, Daniela, et al.
Published: (2025)

Smooth Lower Bounds for Differentially Private Algorithms via Padding-and-Permuting Fingerprinting Codes
by: Peter, Naty, et al.
Published: (2023)

Nearly-Linear Time Private Hypothesis Selection with the Optimal Approximation Factor
by: Aliakbarpour, Maryam, et al.
Published: (2025)

DPSW-Sketch: A Differentially Private Sketch Framework for Frequency Estimation over Sliding Windows (Technical Report)
by: Wang, Yiping, et al.
Published: (2024)

On Differentially Private String Distances
by: Hu, Jerry Yao-Chieh, et al.
Published: (2024)

Efficiently Computing Similarities to Private Datasets
by: Backurs, Arturs, et al.
Published: (2024)

How Private are DP-SGD Implementations?
by: Chua, Lynn, et al.
Published: (2024)

Faster Private Minimum Spanning Trees
by: Pagh, Rasmus, et al.
Published: (2024)

Private Learning of Littlestone Classes, Revisited
by: Lyu, Xin
Published: (2025)

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

Private Continual Counting of Unbounded Streams
by: Jacobsen, Ben, et al.
Published: (2025)

Differentially Private Densest Subgraph Detection
by: Nguyen, Dung, et al.
Published: (2021)

Streaming Private Continual Counting via Binning
by: Andersson, Joel Daniel, et al.
Published: (2024)

Not All Learnable Distribution Classes are Privately Learnable
by: Bun, Mark, et al.
Published: (2024)

Private Geometric Median in Nearly-Linear Time
by: Kumar, Syamantak, et al.
Published: (2025)

PLAN: Variance-Aware Private Mean Estimation
by: Aumüller, Martin, et al.
Published: (2023)

Exact zCDP Characterizations for Fundamental Differentially Private Mechanisms
by: Harrison, Charlie, et al.
Published: (2025)

Privacy-Computation trade-offs in Private Repetition and Metaselection
by: Talwar, Kunal
Published: (2024)

Optimal Differentially Private Sampling of Unbounded Gaussians
by: Iverson, Valentio, et al.
Published: (2025)

Private PAC Learning May be Harder than Online Learning
by: Bun, Mark, et al.
Published: (2024)

Better Private Distribution Testing by Leveraging Unverified Auxiliary Data
by: Aliakbarpour, Maryam, et al.
Published: (2025)

PREAMBLE: Private and Efficient Aggregation via Block Sparse Vectors
by: Asi, Hilal, et al.
Published: (2025)

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

Adaptive Batch Size for Privately Finding Second-Order Stationary Points
by: Liu, Daogao, et al.
Published: (2024)

Private Mean Estimation with Person-Level Differential Privacy
by: Agarwal, Sushant, et al.
Published: (2024)