Saved in:
| Main Authors: | Kalinin, Nikita P., Rehn, Aki, Andersson, Joel Daniel, Honkela, Antti, Lampert, Christoph H. |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.18379 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Back to Square Roots: An Optimal Bound on the Matrix Factorization Error for Multi-Epoch Differentially Private SGD
by: Kalinin, Nikita P., et al.
Published: (2025)
by: Kalinin, Nikita P., et al.
Published: (2025)
Banded Square Root Matrix Factorization for Differentially Private Model Training
by: Kalinin, Nikita P., et al.
Published: (2024)
by: Kalinin, Nikita P., et al.
Published: (2024)
On Optimal Hyperparameters for Differentially Private Deep Transfer Learning
by: Rehn, Aki, et al.
Published: (2025)
by: Rehn, Aki, et al.
Published: (2025)
Learning Rate Scheduling with Matrix Factorization for Private Training
by: Kalinin, Nikita P., et al.
Published: (2025)
by: Kalinin, Nikita P., et al.
Published: (2025)
Mitigating Disparate Impact of Differentially Private Learning through Bounded Adaptive Clipping
by: Zhao, Linzh, et al.
Published: (2025)
by: Zhao, Linzh, et al.
Published: (2025)
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)
Normalized Square Root: Sharper Matrix Factorization Bounds for Differentially Private Continual Counting
by: Henzinger, Monika, et al.
Published: (2025)
by: Henzinger, Monika, et al.
Published: (2025)
DP-λCGD: Efficient Noise Correlation for Differentially Private Model Training
by: Kalinin, Nikita P., et al.
Published: (2026)
by: Kalinin, Nikita P., et al.
Published: (2026)
DP-KAN: Differentially Private Kolmogorov-Arnold Networks
by: Kalinin, Nikita P., et al.
Published: (2024)
by: Kalinin, Nikita P., et al.
Published: (2024)
Noise-Aware Differentially Private Variational Inference
by: Alrawajfeh, Talal, et al.
Published: (2024)
by: Alrawajfeh, Talal, et al.
Published: (2024)
Matrix Factorization for Practical Continual Mean Estimation Under User-Level Differential Privacy
by: Kalinin, Nikita P., et al.
Published: (2026)
by: Kalinin, Nikita P., et al.
Published: (2026)
Continual Release Moment Estimation with Differential Privacy
by: Kalinin, Nikita P., et al.
Published: (2025)
by: Kalinin, Nikita P., et al.
Published: (2025)
Subsampling is not Magic: Why Large Batch Sizes Work for Differentially Private Stochastic Optimisation
by: Räisä, Ossi, et al.
Published: (2024)
by: Räisä, Ossi, et al.
Published: (2024)
Efficient and Scalable Implementation of Differentially Private Deep Learning without Shortcuts
by: Beltran, Sebastian Rodriguez, et al.
Published: (2024)
by: Beltran, Sebastian Rodriguez, et al.
Published: (2024)
Binned Group Algebra Factorization for Differentially Private Continual Counting
by: Henzinger, Monika, et al.
Published: (2025)
by: Henzinger, Monika, et al.
Published: (2025)
A Bias-Variance Decomposition for Ensembles over Multiple Synthetic Datasets
by: Räisä, Ossi, et al.
Published: (2024)
by: Räisä, Ossi, et al.
Published: (2024)
Privacy Leakage via Output Label Space and Differentially Private Continual Learning
by: Tobaben, Marlon, et al.
Published: (2024)
by: Tobaben, Marlon, et al.
Published: (2024)
Beyond Membership: Limitations of Add/Remove Adjacency in Differential Privacy
by: Pradhan, Gauri, et al.
Published: (2025)
by: Pradhan, Gauri, et al.
Published: (2025)
On Reliability of Efficient Membership Inference Vulnerability Evaluation
by: Jälkö, Joonas, et al.
Published: (2026)
by: Jälkö, Joonas, et al.
Published: (2026)
Noise-Aware Differentially Private Regression via Meta-Learning
by: Räisä, Ossi, et al.
Published: (2024)
by: Räisä, Ossi, et al.
Published: (2024)
DP-MicroAdam: Private and Frugal Algorithm for Training and Fine-tuning
by: Hudişteanu, Mihaela, et al.
Published: (2025)
by: Hudişteanu, Mihaela, et al.
Published: (2025)
A Smooth Binary Mechanism for Efficient Private Continual Observation
by: Andersson, Joel Daniel, et al.
Published: (2023)
by: Andersson, Joel Daniel, et al.
Published: (2023)
Empirical Comparison of Membership Inference Attacks in Deep Transfer Learning
by: Bai, Yuxuan, et al.
Published: (2025)
by: Bai, Yuxuan, et al.
Published: (2025)
Notes on Sampled Gaussian Mechanism
by: Kalinin, Nikita P.
Published: (2024)
by: Kalinin, Nikita P.
Published: (2024)
Hyperparameters in Score-Based Membership Inference Attacks
by: Pradhan, Gauri, et al.
Published: (2025)
by: Pradhan, Gauri, et al.
Published: (2025)
Improved Accuracy for Private Continual Cardinality Estimation in Fully Dynamic Streams via Matrix Factorization
by: Andersson, Joel Daniel, et al.
Published: (2026)
by: Andersson, Joel Daniel, et al.
Published: (2026)
Impact of Dataset Properties on Membership Inference Vulnerability of Deep Transfer Learning
by: Tobaben, Marlon, et al.
Published: (2024)
by: Tobaben, Marlon, et al.
Published: (2024)
Streaming Private Continual Counting via Binning
by: Andersson, Joel Daniel, et al.
Published: (2024)
by: Andersson, Joel Daniel, et al.
Published: (2024)
Population Risk Bounds for Kolmogorov-Arnold Networks Trained by DP-SGD with Correlated Noise
by: Wang, Puyu, et al.
Published: (2026)
by: Wang, Puyu, et al.
Published: (2026)
Accuracy-First Rényi Differential Privacy and Post-Processing Immunity
by: Räisä, Ossi, et al.
Published: (2025)
by: Räisä, Ossi, et al.
Published: (2025)
Sampling-Free Privacy Accounting for Matrix Mechanisms under Random Allocation
by: Schuchardt, Jan, et al.
Published: (2026)
by: Schuchardt, Jan, et al.
Published: (2026)
Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes
by: Zakerinia, Hossein, et al.
Published: (2025)
by: Zakerinia, Hossein, et al.
Published: (2025)
Adaptive Sampling and Clipping for Private Worst-Case Group Optimization
by: Cairney-Leeming, Max, et al.
Published: (2026)
by: Cairney-Leeming, Max, et al.
Published: (2026)
Differentially Private Federated $k$-Means Clustering with Server-Side Data
by: Scott, Jonathan, et al.
Published: (2025)
by: Scott, Jonathan, et al.
Published: (2025)
SMMF: Square-Matricized Momentum Factorization for Memory-Efficient Optimization
by: Park, Kwangryeol, et al.
Published: (2024)
by: Park, Kwangryeol, et al.
Published: (2024)
Gaussian DP for Reporting Differential Privacy Guarantees in Machine Learning
by: Gomez, Juan Felipe, et al.
Published: (2025)
by: Gomez, Juan Felipe, et al.
Published: (2025)
$f$-Differential Privacy Filters: Validity and Approximate Solutions
by: Tran, Long, et al.
Published: (2026)
by: Tran, Long, et al.
Published: (2026)
From Low Intrinsic Dimensionality to Non-Vacuous Generalization Bounds in Deep Multi-Task Learning
by: Zakerinia, Hossein, et al.
Published: (2025)
by: Zakerinia, Hossein, et al.
Published: (2025)
Differentially Private In-Context Learning with Nearest Neighbor Search
by: Koskela, Antti, et al.
Published: (2025)
by: Koskela, Antti, et al.
Published: (2025)
Learning Quantized Continuous Controllers for Integer Hardware
by: Kresse, Fabian, et al.
Published: (2025)
by: Kresse, Fabian, et al.
Published: (2025)
Similar Items
-
Back to Square Roots: An Optimal Bound on the Matrix Factorization Error for Multi-Epoch Differentially Private SGD
by: Kalinin, Nikita P., et al.
Published: (2025) -
Banded Square Root Matrix Factorization for Differentially Private Model Training
by: Kalinin, Nikita P., et al.
Published: (2024) -
On Optimal Hyperparameters for Differentially Private Deep Transfer Learning
by: Rehn, Aki, et al.
Published: (2025) -
Learning Rate Scheduling with Matrix Factorization for Private Training
by: Kalinin, Nikita P., et al.
Published: (2025) -
Mitigating Disparate Impact of Differentially Private Learning through Bounded Adaptive Clipping
by: Zhao, Linzh, et al.
Published: (2025)