Imagen de Portada

Breaking the Communication-Privacy-Accuracy Tradeoff with $f$-Differential Privacy

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Jin, Richeng, Su, Zhonggen, Zhong, Caijun, Zhang, Zhaoyang, Quek, Tony, Dai, Huaiyu
Formato:	Preprint
Publicado:	2023
Materias:	Cryptography and Security Information Theory Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Composition Theorems for f-Differential Privacy
por: Fernandes, Natasha, et al.
Publicado: (2025)

Rao Differential Privacy
por: Soto, Carlos
Publicado: (2025)

Privacy-Utility Tradeoffs in Quantum Information Processing
por: Nuradha, Theshani, et al.
Publicado: (2026)

Differentially Private Spectral Graph Clustering: Balancing Privacy, Accuracy, and Efficiency
por: Koskela, Antti, et al.
Publicado: (2025)

Privacy for Fairness: Information Obfuscation for Fair Representation Learning with Local Differential Privacy
por: Xie, Songjie, et al.
Publicado: (2024)

Concentrated Differential Privacy for Bandits
por: Azize, Achraf, et al.
Publicado: (2023)

Correlated Privacy Mechanisms for Differentially Private Distributed Mean Estimation
por: Vithana, Sajani, et al.
Publicado: (2024)

Collaborative Inference over Wireless Channels with Feature Differential Privacy
por: Seif, Mohamed, et al.
Publicado: (2024)

Secure Semantic Communication via Paired Adversarial Residual Networks
por: He, Boxiang, et al.
Publicado: (2024)

On Improving the Composition Privacy Loss in Differential Privacy for Fixed Estimation Error
por: Rameshwar, V. Arvind, et al.
Publicado: (2024)

The Hidden Cost of Correlation: Rethinking Privacy Leakage in Local Differential Privacy
por: Jayawardana, Sandaru, et al.
Publicado: (2025)

Local Differential Privacy with Correlated Noise Achieves Central-DP Optimal Cost
por: Pathegama, Madhura, et al.
Publicado: (2026)

Mitigating Privacy-Utility Trade-off in Decentralized Federated Learning via $f$-Differential Privacy
por: Li, Xiang, et al.
Publicado: (2025)

Optimal Regret of Bernoulli Bandits under Global Differential Privacy
por: Azize, Achraf, et al.
Publicado: (2025)

Generalized Rainbow Differential Privacy
por: Gu, Yuzhou, et al.
Publicado: (2023)

Inference Privacy: Properties and Mechanisms
por: Tian, Fengwei, et al.
Publicado: (2024)

TernaryVote: Differentially Private, Communication Efficient, and Byzantine Resilient Distributed Optimization on Heterogeneous Data
por: Jin, Richeng, et al.
Publicado: (2024)

Multi-Agent-Driven Cognitive Secure Communications in Satellite-Terrestrial Networks
por: Ling, Yujie, et al.
Publicado: (2026)

Over-the-Air Collaborative Inference with Feature Differential Privacy
por: Seif, Mohamed, et al.
Publicado: (2024)

Correlated-Sequence Differential Privacy
por: Luo, Yifan, et al.
Publicado: (2025)

On the Price of Differential Privacy for Spectral Clustering over Stochastic Block Models
por: Koskela, Antti, et al.
Publicado: (2025)

Dobrushin Coefficients of Private Mechanisms Beyond Local Differential Privacy
por: Grosse, Leonhard, et al.
Publicado: (2026)

Optimality of Staircase Mechanisms for Vector Queries under Differential Privacy
por: Melbourne, James, et al.
Publicado: (2026)

An Efficient Difference-of-Convex Solver for Privacy Funnel
por: Huang, Teng-Hui, et al.
Publicado: (2024)

Evaluating Differential Privacy on Correlated Datasets Using Pointwise Maximal Leakage
por: Saeidian, Sara, et al.
Publicado: (2025)

Strict Optimality of Frequency and Distribution Estimation Under Local Differential Privacy
por: Pan, Mingen
Publicado: (2026)

Privacy-Preserving Graph Embedding based on Local Differential Privacy
por: Li, Zening, et al.
Publicado: (2023)

STAMP: Selective Task-Aware Mechanism for Text Privacy
por: Tian, Fengwei, et al.
Publicado: (2026)

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

Analysis of Shuffling Beyond Pure Local Differential Privacy
por: Takagi, Shun, et al.
Publicado: (2026)

Privacy Against Agnostic Inference Attacks in Vertical Federated Learning
por: Varasteh, Morteza
Publicado: (2023)

On Polynomial Approximations for Privacy-Preserving and Verifiable ReLU Networks
por: Ali, Ramy E., et al.
Publicado: (2020)

Meeting Utility Constraints in Differential Privacy: A Privacy-Boosting Approach
por: Jiang, Bo, et al.
Publicado: (2024)

Concurrent Composition for Interactive Differential Privacy with Adaptive Privacy-Loss Parameters
por: Haney, Samuel, et al.
Publicado: (2023)

Private Sum Computation: Trade-Offs between Communication, Randomness, and Privacy
por: Chou, Remi A., et al.
Publicado: (2026)

Quantum Pufferfish Privacy: A Flexible Privacy Framework for Quantum Systems
por: Nuradha, Theshani, et al.
Publicado: (2023)

Fundamental Limit of Discrete Distribution Estimation under Utility-Optimized Local Differential Privacy
por: Yoon, Sun-Moon, et al.
Publicado: (2025)

Byzantine Outside, Curious Inside: Reconstructing Data Through Malicious Updates
por: Yue, Kai, et al.
Publicado: (2025)

When Does Quantum Differential Privacy Compose?
por: Alabi, Daniel, et al.
Publicado: (2026)

$α$-Mutual Information: A Tunable Privacy Measure for Privacy Protection in Data Sharing
por: Asl, MirHamed Jafarzadeh, et al.
Publicado: (2023)