:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	McKenna, Ryan, Mullins, Brett, Sheldon, Daniel, Miklau, Gerome
Formato:	Preprint
Publicado:	2022
Materias:	Databases
Acceso en línea:	https://arxiv.org/abs/2201.12677
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

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

Fast Private Adaptive Query Answering for Large Data Domains
por: Fuentes, Miguel, et al.
Publicado: (2026)

Measure-Observe-Remeasure: An Interactive Paradigm for Differentially-Private Exploratory Analysis
por: Nanayakkara, Priyanka, et al.
Publicado: (2024)

Scaling up the Banded Matrix Factorization Mechanism for Differentially Private ML
por: McKenna, Ryan
Publicado: (2024)

Releasing Large-Scale Human Mobility Histograms with Differential Privacy
por: Bian, Christopher, et al.
Publicado: (2024)

Differentially Private Synthetic Data Generation for Relational Databases
por: Alimohammadi, Kaveh, et al.
Publicado: (2024)

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

PGB: Benchmarking Differentially Private Synthetic Graph Generation Algorithms
por: Liu, Shang, et al.
Publicado: (2024)

Are Data Experts Buying into Differentially Private Synthetic Data? Gathering Community Perspectives
por: Rosenblatt, Lucas, et al.
Publicado: (2024)

Benchmarking Differentially Private Tabular Data Synthesis
por: Chen, Kai, et al.
Publicado: (2025)

Differentially Private Data Generation with Missing Data
por: Mohapatra, Shubhankar, et al.
Publicado: (2023)

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data?
por: Swanberg, Marika, et al.
Publicado: (2025)

Mayfly: Private Aggregate Insights from Ephemeral Streams of On-Device User Data
por: Bian, Christopher, et al.
Publicado: (2024)

Structure Selection for Fairness-Constrained Differentially Private Data Synthesis
por: Ghahramanpour, Naeim, et al.
Publicado: (2026)

An Algorithm for Streaming Differentially Private Data
por: Kumar, Girish, et al.
Publicado: (2024)

Differentially Private Inductive Miner
por: Schulze, Max, et al.
Publicado: (2024)

Differentially Private Explanations for Clusters
por: Gilad, Amir, et al.
Publicado: (2025)

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

Privately Answering Queries on Skewed Data via Per Record Differential Privacy
por: Seeman, Jeremy, et al.
Publicado: (2023)

Differentially Private Stream Processing at Scale
por: Zhang, Bing, et al.
Publicado: (2023)

Differentially Private Learned Indexes
por: Du, Jianzhang, et al.
Publicado: (2024)

Qrlew: Rewriting SQL into Differentially Private SQL
por: Grislain, Nicolas, et al.
Publicado: (2024)

Privately Fine-Tuned LLMs Preserve Temporal Dynamics in Tabular Data
por: Rosenblatt, Lucas, et al.
Publicado: (2026)

Relational to RDF Data Migration by Query Co-Evaluation
por: Wisnesky, Ryan, et al.
Publicado: (2024)

DP-λCGD: Efficient Noise Correlation for Differentially Private Model Training
por: Kalinin, Nikita P., et al.
Publicado: (2026)

Iterative Forgetting: Online Data Stream Regression Using Database-Inspired Adaptive Granulation
por: Kathiriya, Niket, et al.
Publicado: (2024)

Differentially Private Selection using Smooth Sensitivity
por: Chaves, Iago, et al.
Publicado: (2025)

PE-means: Improved Differentially Private $k$-means Clustering through Private Evolution
por: Humphries, Thomas, et al.
Publicado: (2026)

Interpreting the Error of Differentially Private Median Queries through Randomization Intervals
por: Humphries, Thomas, et al.
Publicado: (2026)

Back to Square Roots: An Optimal Bound on the Matrix Factorization Error for Multi-Epoch Differentially Private SGD
por: Kalinin, Nikita P., et al.
Publicado: (2025)

Synthetic Clarification and Correction Dialogues about Data-Centric Tasks -- A Teacher-Student Approach
por: Poelitz, Christian, et al.
Publicado: (2025)

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

It's My Data Too: Private ML for Datasets with Multi-User Training Examples
por: Ganesh, Arun, et al.
Publicado: (2025)

Correlated Noise Mechanisms for Differentially Private Learning
por: Pillutla, Krishna, et al.
Publicado: (2025)

GenIE - Simulator-Driven Iterative Data Exploration for Scientific Discovery
por: Colaco, Ashwin Gerard, et al.
Publicado: (2025)

FHAIM: Fully Homomorphic AIM For Private Synthetic Data Generation
por: Kumar, Mayank, et al.
Publicado: (2026)

Practical and Accurate Local Edge Differentially Private Graph Algorithms
por: Mundra, Pranay, et al.
Publicado: (2025)

Algebraic Data Integration
por: Schultz, Patrick, et al.
Publicado: (2015)

DPSQL+: A Differentially Private SQL Library with a Minimum Frequency Rule
por: Matsumoto, Tomoya, et al.
Publicado: (2026)

ORQ: Complex Analytics on Private Data with Strong Security Guarantees
por: Baum, Eli, et al.
Publicado: (2025)