Saved in:
| Main Authors: | Parsarad, Shiva, Wagner, Isabel |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.22515 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Synthetic Data: Revisiting the Privacy-Utility Trade-off
by: Sarmin, Fatima Jahan, et al.
Published: (2024)
by: Sarmin, Fatima Jahan, et al.
Published: (2024)
Preserving Privacy and Utility in LLM-Based Product Recommendations
by: Khezresmaeilzadeh, Tina, et al.
Published: (2025)
by: Khezresmaeilzadeh, Tina, et al.
Published: (2025)
Meta-Learning and Targeted Differential Privacy to Improve the Accuracy-Privacy Trade-off in Recommendations
by: Müllner, Peter, et al.
Published: (2026)
by: Müllner, Peter, et al.
Published: (2026)
Mitigating Privacy-Utility Trade-off in Decentralized Federated Learning via $f$-Differential Privacy
by: Li, Xiang, et al.
Published: (2025)
by: Li, Xiang, et al.
Published: (2025)
Privacy versus Emotion Preservation Trade-offs in Emotion-Preserving Speaker Anonymization
by: Cai, Zexin, et al.
Published: (2024)
by: Cai, Zexin, et al.
Published: (2024)
Privacy-Preserving Generative Models: A Comprehensive Survey
by: Padariya, Debalina, et al.
Published: (2025)
by: Padariya, Debalina, et al.
Published: (2025)
Federated Latent Factor Model for Bias-Aware Recommendation with Privacy-Preserving
by: Gao, Junxiang, et al.
Published: (2025)
by: Gao, Junxiang, et al.
Published: (2025)
Misclassification Rate and Privacy-Utility Trade-offs in Graph Convolutional Networks via Subsampling Stability
by: Zhang, Yexin, et al.
Published: (2026)
by: Zhang, Yexin, et al.
Published: (2026)
Enhancing Trade-offs in Privacy, Utility, and Computational Efficiency through MUltistage Sampling Technique (MUST)
by: Zhao, Xingyuan, et al.
Published: (2023)
by: Zhao, Xingyuan, et al.
Published: (2023)
A Framework for Evaluating Privacy-Utility Trade-off in Vertical Federated Learning
by: Kang, Yan, et al.
Published: (2022)
by: Kang, Yan, et al.
Published: (2022)
Revisiting Privacy, Utility, and Efficiency Trade-offs when Fine-Tuning Large Language Models
by: Das, Soumi, et al.
Published: (2025)
by: Das, Soumi, et al.
Published: (2025)
Optimizing Privacy-Utility Trade-off in Decentralized Learning with Generalized Correlated Noise
by: Rodio, Angelo, et al.
Published: (2025)
by: Rodio, Angelo, et al.
Published: (2025)
The Privacy-Utility Trade-Off of Location Tracking in Ad Personalization
by: Mosaffa, Mohammad, et al.
Published: (2026)
by: Mosaffa, Mohammad, et al.
Published: (2026)
Differential Privacy for Anomaly Detection: Analyzing the Trade-off Between Privacy and Explainability
by: Ezzeddine, Fatima, et al.
Published: (2024)
by: Ezzeddine, Fatima, et al.
Published: (2024)
FedEM: A Privacy-Preserving Framework for Concurrent Utility Preservation in Federated Learning
by: Xu, Mingcong, et al.
Published: (2025)
by: Xu, Mingcong, et al.
Published: (2025)
Privacy-Utility Trade-off in Data Publication: A Bilevel Optimization Framework with Curvature-Guided Perturbation
by: Yin, Yi, et al.
Published: (2025)
by: Yin, Yi, et al.
Published: (2025)
Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-off
by: Li, Yuecheng, et al.
Published: (2024)
by: Li, Yuecheng, et al.
Published: (2024)
A Unified Learn-to-Distort-Data Framework for Privacy-Utility Trade-off in Trustworthy Federated Learning
by: Zhang, Xiaojin, et al.
Published: (2024)
by: Zhang, Xiaojin, et al.
Published: (2024)
An Interactive Framework for Finding the Optimal Trade-off in Differential Privacy
by: Yang, Yaohong, et al.
Published: (2025)
by: Yang, Yaohong, et al.
Published: (2025)
Privacy Blur: Quantifying Privacy and Utility for Image Data Release
by: Mahloujifar, Saeed, et al.
Published: (2025)
by: Mahloujifar, Saeed, et al.
Published: (2025)
A Privacy Preserving System for Movie Recommendations Using Federated Learning
by: Neumann, David, et al.
Published: (2023)
by: Neumann, David, et al.
Published: (2023)
Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy
by: Chen, Wei-Ning, et al.
Published: (2024)
by: Chen, Wei-Ning, et al.
Published: (2024)
Preempting Text Sanitization Utility in Resource-Constrained Privacy-Preserving LLM Interactions
by: Carpentier, Robin, et al.
Published: (2024)
by: Carpentier, Robin, et al.
Published: (2024)
Privacy-Preserving Orthogonal Aggregation for Guaranteeing Gender Fairness in Federated Recommendation
by: Zhang, Siqing, et al.
Published: (2024)
by: Zhang, Siqing, et al.
Published: (2024)
Privacy-Accuracy Trade-offs in High-Dimensional LASSO under Perturbation Mechanisms
by: Sakata, Ayaka, et al.
Published: (2026)
by: Sakata, Ayaka, et al.
Published: (2026)
Privacy-Preserving Race/Ethnicity Estimation for Algorithmic Bias Measurement in the U.S
by: Badrinarayanan, Saikrishna, et al.
Published: (2024)
by: Badrinarayanan, Saikrishna, et al.
Published: (2024)
Enhancing the Utility of Privacy-Preserving Cancer Classification using Synthetic Data
by: Osuala, Richard, et al.
Published: (2024)
by: Osuala, Richard, et al.
Published: (2024)
Striking the Perfect Balance: Preserving Privacy While Boosting Utility in Collaborative Medical Prediction Platforms
by: Lin, Shao-Bo, et al.
Published: (2025)
by: Lin, Shao-Bo, et al.
Published: (2025)
Privacy-Preserving Multimodal News Recommendation through Federated Learning
by: Khalaj, Mehdi, et al.
Published: (2025)
by: Khalaj, Mehdi, et al.
Published: (2025)
The Users' Perspective on the Privacy-Utility Trade-offs in Health Recommender Systems
by: Valdez, André Calero, et al.
Published: (2018)
by: Valdez, André Calero, et al.
Published: (2018)
Privacy-Preserving Conformal Prediction Under Local Differential Privacy
by: Penso, Coby, et al.
Published: (2025)
by: Penso, Coby, et al.
Published: (2025)
A Survey of Personalized Federated Foundation Models for Privacy-Preserving Recommendation
by: Li, Zhiwei, et al.
Published: (2025)
by: Li, Zhiwei, et al.
Published: (2025)
Characterizing the Accuracy-Communication-Privacy Trade-off in Distributed Stochastic Convex Optimization
by: Salgia, Sudeep, et al.
Published: (2025)
by: Salgia, Sudeep, et al.
Published: (2025)
Federated Learning in Genetics: Extended Analysis of Accuracy, Performance and Privacy Trade-offs
by: Hannemann, Anika, et al.
Published: (2024)
by: Hannemann, Anika, et al.
Published: (2024)
Connecting Thompson Sampling and UCB: Towards More Efficient Trade-offs Between Privacy and Regret
by: Hu, Bingshan, et al.
Published: (2025)
by: Hu, Bingshan, et al.
Published: (2025)
FedPF: Accurate Target Privacy Preserving Federated Learning Balancing Fairness and Utility
by: Sun, Kangkang, et al.
Published: (2025)
by: Sun, Kangkang, et al.
Published: (2025)
Accuracy-Privacy Trade-off in the Mitigation of Membership Inference Attack in Federated Learning
by: Ahamed, Sayyed Farid, et al.
Published: (2024)
by: Ahamed, Sayyed Farid, et al.
Published: (2024)
Graph Federated Unlearning for Privacy Preservation
by: Ma, Ruotong, et al.
Published: (2026)
by: Ma, Ruotong, et al.
Published: (2026)
Privacy-Preserving Personalization in Education: A Federated Recommender System for Student Performance Prediction
by: Tertulino, Rodrigo, et al.
Published: (2025)
by: Tertulino, Rodrigo, et al.
Published: (2025)
Privacy-Preserving Transformers: SwiftKey's Differential Privacy Implementation
by: Abouelenin, Abdelrahman, et al.
Published: (2025)
by: Abouelenin, Abdelrahman, et al.
Published: (2025)
Similar Items
-
Synthetic Data: Revisiting the Privacy-Utility Trade-off
by: Sarmin, Fatima Jahan, et al.
Published: (2024) -
Preserving Privacy and Utility in LLM-Based Product Recommendations
by: Khezresmaeilzadeh, Tina, et al.
Published: (2025) -
Meta-Learning and Targeted Differential Privacy to Improve the Accuracy-Privacy Trade-off in Recommendations
by: Müllner, Peter, et al.
Published: (2026) -
Mitigating Privacy-Utility Trade-off in Decentralized Federated Learning via $f$-Differential Privacy
by: Li, Xiang, et al.
Published: (2025) -
Privacy versus Emotion Preservation Trade-offs in Emotion-Preserving Speaker Anonymization
by: Cai, Zexin, et al.
Published: (2024)