Privacy Amplification for BandMF via $b$-Min-Sep Subsampling
Fuente:
arXiv
Guardado en:
| Autores principales: | Dong, Andy, Ganesh, Arun |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Unified Mechanism-Specific Amplification by Subsampling and Group Privacy Amplification
por: Schuchardt, Jan, et al.
Publicado: (2024)
por: Schuchardt, Jan, et al.
Publicado: (2024)
Near Exact Privacy Amplification for Matrix Mechanisms
por: Choquette-Choo, Christopher A., et al.
Publicado: (2024)
por: Choquette-Choo, Christopher A., et al.
Publicado: (2024)
Privacy Amplification for Matrix Mechanisms
por: Choquette-Choo, Christopher A., et al.
Publicado: (2023)
por: Choquette-Choo, Christopher A., et al.
Publicado: (2023)
Tighter Privacy Analysis for Truncated Poisson Sampling
por: Ganesh, Arun
Publicado: (2025)
por: Ganesh, Arun
Publicado: (2025)
Privacy Amplification by Structured Subsampling for Deep Differentially Private Time Series Forecasting
por: Schuchardt, Jan, et al.
Publicado: (2025)
por: Schuchardt, Jan, et al.
Publicado: (2025)
Improving Statistical Privacy by Subsampling
por: Breutigam, Dennis, et al.
Publicado: (2025)
por: Breutigam, Dennis, et al.
Publicado: (2025)
Leveraging Randomness in Model and Data Partitioning for Privacy Amplification
por: Dong, Andy, et al.
Publicado: (2025)
por: Dong, Andy, et al.
Publicado: (2025)
Continual Release of Densest Subgraphs: Privacy Amplification & Sublinear Space via Subsampling
por: Zhou, Felix
Publicado: (2025)
por: Zhou, Felix
Publicado: (2025)
Calibrating Noise for Group Privacy in Subsampled Mechanisms
por: Jiang, Yangfan, et al.
Publicado: (2024)
por: Jiang, Yangfan, et al.
Publicado: (2024)
Less Random, More Private: What is the Optimal Subsampling Scheme for DP-SGD?
por: Dong, Andy, et al.
Publicado: (2026)
por: Dong, Andy, et al.
Publicado: (2026)
Tight Group-Level DP Guarantees for DP-SGD with Sampling via Mixture of Gaussians Mechanisms
por: Ganesh, Arun
Publicado: (2024)
por: Ganesh, Arun
Publicado: (2024)
Privacy Amplification via Shuffling: Unified, Simplified, and Tightened
por: Wang, Shaowei, et al.
Publicado: (2023)
por: Wang, Shaowei, et al.
Publicado: (2023)
Decomposition-Based Optimal Bounds for Privacy Amplification via Shuffling
por: Su, Pengcheng, et al.
Publicado: (2025)
por: Su, Pengcheng, et al.
Publicado: (2025)
Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization
por: Ghazi, Badih, et al.
Publicado: (2024)
por: Ghazi, Badih, et al.
Publicado: (2024)
Personalized Privacy Amplification via Importance Sampling
por: Fay, Dominik, et al.
Publicado: (2023)
por: Fay, Dominik, et al.
Publicado: (2023)
Privacy Amplification for the Gaussian Mechanism via Bounded Support
por: Hu, Shengyuan, et al.
Publicado: (2024)
por: Hu, Shengyuan, et al.
Publicado: (2024)
A Generalized Shuffle Framework for Privacy Amplification: Strengthening Privacy Guarantees and Enhancing Utility
por: Chen, E, et al.
Publicado: (2023)
por: Chen, E, et al.
Publicado: (2023)
Rényi Pufferfish Privacy: General Additive Noise Mechanisms and Privacy Amplification by Iteration
por: Pierquin, Clément, et al.
Publicado: (2023)
por: Pierquin, Clément, et al.
Publicado: (2023)
Avoiding Pitfalls for Privacy Accounting of Subsampled Mechanisms under Composition
por: Lebeda, Christian Janos, et al.
Publicado: (2024)
por: Lebeda, Christian Janos, et al.
Publicado: (2024)
randextract: a Reference Library to Test and Validate Privacy Amplification Implementations
por: Veiga, Iyán Méndez, et al.
Publicado: (2025)
por: Veiga, Iyán Méndez, et al.
Publicado: (2025)
Privacy Amplification Through Synthetic Data: Insights from Linear Regression
por: Pierquin, Clément, et al.
Publicado: (2025)
por: Pierquin, Clément, et al.
Publicado: (2025)
Blockchain Amplification Attack
por: Tsuchiya, Taro, et al.
Publicado: (2024)
por: Tsuchiya, Taro, et al.
Publicado: (2024)
Practical Differentially Private Hyperparameter Tuning with Subsampling
por: Koskela, Antti, et al.
Publicado: (2023)
por: Koskela, Antti, et al.
Publicado: (2023)
Shielding Latent Face Representations From Privacy Attacks
por: Kaushik, Arjun Ramesh, et al.
Publicado: (2025)
por: Kaushik, Arjun Ramesh, et al.
Publicado: (2025)
Hush! Protecting Secrets During Model Training: An Indistinguishability Approach
por: Ganesh, Arun, et al.
Publicado: (2025)
por: Ganesh, Arun, et al.
Publicado: (2025)
On Design Principles for Private Adaptive Optimizers
por: Ganesh, Arun, et al.
Publicado: (2025)
por: Ganesh, Arun, et al.
Publicado: (2025)
Public-Key Encryption from the MinRank Problem
por: Chatterjee, Rohit, et al.
Publicado: (2025)
por: Chatterjee, Rohit, et al.
Publicado: (2025)
MinRank Gabidulin encryption scheme on matrix codes
por: Aragon, Nicolas, et al.
Publicado: (2024)
por: Aragon, Nicolas, et al.
Publicado: (2024)
It's Our Loss: No Privacy Amplification for Hidden State DP-SGD With Non-Convex Loss
por: Annamalai, Meenatchi Sundaram Muthu Selva
Publicado: (2024)
por: Annamalai, Meenatchi Sundaram Muthu Selva
Publicado: (2024)
Towards the Impossibility of Non-Signalling Privacy Amplification from Time-Like Ordering Constraints
por: Arnon, Rotem, et al.
Publicado: (2012)
por: Arnon, Rotem, et al.
Publicado: (2012)
One Key Good, L Keys Better: List Decoding Meets Quantum Privacy Amplification
por: Kulkarni, Prateek P.
Publicado: (2026)
por: Kulkarni, Prateek P.
Publicado: (2026)
Whose Narrative is it Anyway? A KV Cache Manipulation Attack
por: Ganesh, Mukkesh, et al.
Publicado: (2025)
por: Ganesh, Mukkesh, et al.
Publicado: (2025)
Optimal Rates for $O(1)$-Smooth DP-SCO with a Single Epoch and Large Batches
por: Choquette-Choo, Christopher A., et al.
Publicado: (2024)
por: Choquette-Choo, Christopher A., et al.
Publicado: (2024)
AgentCrypt: Advancing Privacy and (Secure) Computation in AI Agent Collaboration
por: Karthikeyan, Harish, et al.
Publicado: (2025)
por: Karthikeyan, Harish, et al.
Publicado: (2025)
Privacy Preservation in Gen AI Applications
por: S, Swetha, et al.
Publicado: (2025)
por: S, Swetha, et al.
Publicado: (2025)
Optimizing Linear Correctors: A Tight Output Min-Entropy Bound and Selection Technique
por: Grujić, Miloš, et al.
Publicado: (2023)
por: Grujić, Miloš, et al.
Publicado: (2023)
Privacy Amplification Persists under Unlimited Synthetic Data Release
por: Pierquin, Clément, et al.
Publicado: (2026)
por: Pierquin, Clément, et al.
Publicado: (2026)
Detecting Adversarial Data via Provable Adversarial Noise Amplification
por: Mumcu, Furkan, et al.
Publicado: (2026)
por: Mumcu, Furkan, et al.
Publicado: (2026)
Data-Driven Subsampling in the Presence of an Adversarial Actor
por: Jameel, Abu Shafin Mohammad Mahdee, et al.
Publicado: (2024)
por: Jameel, Abu Shafin Mohammad Mahdee, et al.
Publicado: (2024)
EditMF: Drawing an Invisible Fingerprint for Your Large Language Models
por: Wu, Jiaxuan, et al.
Publicado: (2025)
por: Wu, Jiaxuan, et al.
Publicado: (2025)
Ejemplares similares
-
Unified Mechanism-Specific Amplification by Subsampling and Group Privacy Amplification
por: Schuchardt, Jan, et al.
Publicado: (2024) -
Near Exact Privacy Amplification for Matrix Mechanisms
por: Choquette-Choo, Christopher A., et al.
Publicado: (2024) -
Privacy Amplification for Matrix Mechanisms
por: Choquette-Choo, Christopher A., et al.
Publicado: (2023) -
Tighter Privacy Analysis for Truncated Poisson Sampling
por: Ganesh, Arun
Publicado: (2025) -
Privacy Amplification by Structured Subsampling for Deep Differentially Private Time Series Forecasting
por: Schuchardt, Jan, et al.
Publicado: (2025)