Copertina

An Interactive Framework for Finding the Optimal Trade-off in Differential Privacy

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Yang, Yaohong, Rehn, Aki, Katt, Sammie, Honkela, Antti, Kaski, Samuel
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Multi-Objective Bayesian Optimization via Adaptive \varepsilon-Constraints Decomposition
di: Yang, Yaohong, et al.
Pubblicazione: (2026)

On Optimal Hyperparameters for Differentially Private Deep Transfer Learning
di: Rehn, Aki, et al.
Pubblicazione: (2025)

More Than Irrational: Modeling Belief-Biased Agents
di: Zhu, Yifan, et al.
Pubblicazione: (2025)

Mitigating Disparate Impact of Differentially Private Learning through Bounded Adaptive Clipping
di: Zhao, Linzh, et al.
Pubblicazione: (2025)

Beyond Square Roots: Explicit Memory-Efficient Factorization for Multi-Epoch Private Learning
di: Kalinin, Nikita P., et al.
Pubblicazione: (2026)

Beyond Membership: Limitations of Add/Remove Adjacency in Differential Privacy
di: Pradhan, Gauri, et al.
Pubblicazione: (2025)

Noise-Aware Differentially Private Variational Inference
di: Alrawajfeh, Talal, et al.
Pubblicazione: (2024)

A Bias-Variance Decomposition for Ensembles over Multiple Synthetic Datasets
di: Räisä, Ossi, et al.
Pubblicazione: (2024)

Subsampling is not Magic: Why Large Batch Sizes Work for Differentially Private Stochastic Optimisation
di: Räisä, Ossi, et al.
Pubblicazione: (2024)

Privacy Leakage via Output Label Space and Differentially Private Continual Learning
di: Tobaben, Marlon, et al.
Pubblicazione: (2024)

Gaussian DP for Reporting Differential Privacy Guarantees in Machine Learning
di: Gomez, Juan Felipe, et al.
Pubblicazione: (2025)

Accuracy-First Rényi Differential Privacy and Post-Processing Immunity
di: Räisä, Ossi, et al.
Pubblicazione: (2025)

Differential Privacy for Anomaly Detection: Analyzing the Trade-off Between Privacy and Explainability
di: Ezzeddine, Fatima, et al.
Pubblicazione: (2024)

Empirical Comparison of Membership Inference Attacks in Deep Transfer Learning
di: Bai, Yuxuan, et al.
Pubblicazione: (2025)

Hyperparameters in Score-Based Membership Inference Attacks
di: Pradhan, Gauri, et al.
Pubblicazione: (2025)

On Reliability of Efficient Membership Inference Vulnerability Evaluation
di: Jälkö, Joonas, et al.
Pubblicazione: (2026)

Meta-Learning and Targeted Differential Privacy to Improve the Accuracy-Privacy Trade-off in Recommendations
di: Müllner, Peter, et al.
Pubblicazione: (2026)

Efficient and Scalable Implementation of Differentially Private Deep Learning without Shortcuts
di: Beltran, Sebastian Rodriguez, et al.
Pubblicazione: (2024)

Auditing Differential Privacy Guarantees Using Density Estimation
di: Koskela, Antti, et al.
Pubblicazione: (2024)

TSGM: A Flexible Framework for Generative Modeling of Synthetic Time Series
di: Nikitin, Alexander, et al.
Pubblicazione: (2023)

GegenbauerNet: Finding the Optimal Compromise in the GNN Flexibility-Stability Trade-off
di: Goksu, Huseyin
Pubblicazione: (2025)

$f$-Differential Privacy Filters: Validity and Approximate Solutions
di: Tran, Long, et al.
Pubblicazione: (2026)

Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy
di: Chen, Wei-Ning, et al.
Pubblicazione: (2024)

Noise-Aware Differentially Private Regression via Meta-Learning
di: Räisä, Ossi, et al.
Pubblicazione: (2024)

Impact of Dataset Properties on Membership Inference Vulnerability of Deep Transfer Learning
di: Tobaben, Marlon, et al.
Pubblicazione: (2024)

Privacy-Utility-Bias Trade-offs for Privacy-Preserving Recommender Systems
di: Parsarad, Shiva, et al.
Pubblicazione: (2025)

Synthetic Data: Revisiting the Privacy-Utility Trade-off
di: Sarmin, Fatima Jahan, et al.
Pubblicazione: (2024)

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

Convex Approximation of Two-Layer ReLU Networks for Hidden State Differential Privacy
di: Romijnders, Rob, et al.
Pubblicazione: (2024)

Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-off
di: Li, Yuecheng, et al.
Pubblicazione: (2024)

A Framework for Evaluating Privacy-Utility Trade-off in Vertical Federated Learning
di: Kang, Yan, et al.
Pubblicazione: (2022)

Improving the Privacy and Practicality of Objective Perturbation for Differentially Private Linear Learners
di: Redberg, Rachel, et al.
Pubblicazione: (2023)

Finding Optimal Trading History in Reinforcement Learning for Stock Market Trading
di: Montazeri, Sina, et al.
Pubblicazione: (2025)

Online Tensor Learning: Computational and Statistical Trade-offs, Adaptivity and Optimal Regret
di: Li, Jingyang, et al.
Pubblicazione: (2023)

Differential Privacy Analysis of Decentralized Gossip Averaging under Varying Threat Models
di: Koskela, Antti, et al.
Pubblicazione: (2025)

A Theory of Random Graph Shift in Truncated-Spectrum vRKHS
di: Wan, Zhang, et al.
Pubblicazione: (2026)

Bayesian Meta-Learning with Expert Feedback for Task-Shift Adaptation through Causal Embeddings
di: Mäkinen, Lotta, et al.
Pubblicazione: (2026)

Elicitation-Augmented Bayesian Optimization
di: Haltia, Alvar, et al.
Pubblicazione: (2026)

Privacy-Accuracy Trade-offs in High-Dimensional LASSO under Perturbation Mechanisms
di: Sakata, Ayaka, et al.
Pubblicazione: (2026)

Shapley Machine: A Game-Theoretic Framework for N-Agent Ad Hoc Teamwork
di: Wang, Jianhong, et al.
Pubblicazione: (2025)