Saved in:
| Main Authors: | Romijnders, Rob, Derakhshani, Mohammad Mahdi, Petit, Jonathan, Welling, Max, Louizos, Christos, Asano, Yuki M. |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2602.05012 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Protect Your Score: Contact Tracing With Differential Privacy Guarantees
by: Romijnders, Rob, et al.
Published: (2023)
by: Romijnders, Rob, et al.
Published: (2023)
DNA: Differentially private Neural Augmentation for contact tracing
by: Romijnders, Rob, et al.
Published: (2024)
by: Romijnders, Rob, et al.
Published: (2024)
A Probabilistic Approach to Pose Synchronization for Multi-Reference Alignment with Applications to MIMO Wireless Communication Systems
by: Romijnders, Rob, et al.
Published: (2025)
by: Romijnders, Rob, et al.
Published: (2025)
NoEsis: Differentially Private Knowledge Transfer in Modular LLM Adaptation
by: Romijnders, Rob, et al.
Published: (2025)
by: Romijnders, Rob, et al.
Published: (2025)
Convex Approximation of Two-Layer ReLU Networks for Hidden State Differential Privacy
by: Romijnders, Rob, et al.
Published: (2024)
by: Romijnders, Rob, et al.
Published: (2024)
Private Geometric Median
by: Haghifam, Mahdi, et al.
Published: (2024)
by: Haghifam, Mahdi, et al.
Published: (2024)
Stable Diffusion-based Data Augmentation for Federated Learning with Non-IID Data
by: Morafah, Mahdi, et al.
Published: (2024)
by: Morafah, Mahdi, et al.
Published: (2024)
On Sampling Strategies for Spectral Model Sharding
by: Korzhenkov, Denis, et al.
Published: (2024)
by: Korzhenkov, Denis, et al.
Published: (2024)
Adaptive Mesh-Quantization for Neural PDE Solvers
by: Dool, Winfried van den, et al.
Published: (2025)
by: Dool, Winfried van den, et al.
Published: (2025)
A Mutual Information Perspective on Federated Contrastive Learning
by: Louizos, Christos, et al.
Published: (2024)
by: Louizos, Christos, et al.
Published: (2024)
Guarding the Meaning: Self-Supervised Training for Semantic Robustness in Guard Models
by: Pinneri, Cristina, et al.
Published: (2025)
by: Pinneri, Cristina, et al.
Published: (2025)
Variational Learning ISTA
by: Massoli, Fabio Valerio, et al.
Published: (2024)
by: Massoli, Fabio Valerio, et al.
Published: (2024)
Non-exchangeable Conformal Prediction with Optimal Transport: Tackling Distribution Shifts with Unlabeled Data
by: Correia, Alvaro H. C., et al.
Published: (2025)
by: Correia, Alvaro H. C., et al.
Published: (2025)
Tracking the Best Expert Privately
by: Saha, Aadirupa, et al.
Published: (2025)
by: Saha, Aadirupa, et al.
Published: (2025)
Masks Can Be Distracting: On Context Comprehension in Diffusion Language Models
by: Piskorz, Julianna, et al.
Published: (2025)
by: Piskorz, Julianna, et al.
Published: (2025)
Privacy Without Losing Place: A Paradigm for Private Retrieval in Spatial RAGs
by: Edemacu, Kennedy, et al.
Published: (2026)
by: Edemacu, Kennedy, et al.
Published: (2026)
On Adaptivity in Zeroth-Order Optimization
by: Dbouk, Hassan, et al.
Published: (2026)
by: Dbouk, Hassan, et al.
Published: (2026)
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation
by: Brown, Gavin, et al.
Published: (2021)
by: Brown, Gavin, et al.
Published: (2021)
From Private to Public: Benchmarking GANs in the Context of Private Time Series Classification
by: Mercier, Dominique, et al.
Published: (2023)
by: Mercier, Dominique, et al.
Published: (2023)
Differentially Private Covariate Balancing Causal Inference
by: Ohnishi, Yuki, et al.
Published: (2024)
by: Ohnishi, Yuki, et al.
Published: (2024)
Differentially Private Training of Mixture of Experts Models
by: Tholoniat, Pierre, et al.
Published: (2024)
by: Tholoniat, Pierre, et al.
Published: (2024)
N-Parties Private Structure and Parameter Learning for Sum-Product Networks
by: Heilmann, Xenia, et al.
Published: (2025)
by: Heilmann, Xenia, et al.
Published: (2025)
InterroGate: Learning to Share, Specialize, and Prune Representations for Multi-task Learning
by: Bejnordi, Babak Ehteshami, et al.
Published: (2024)
by: Bejnordi, Babak Ehteshami, et al.
Published: (2024)
Approximating Full Conformal Prediction for Neural Network Regression with Gauss-Newton Influence
by: Tailor, Dharmesh, et al.
Published: (2025)
by: Tailor, Dharmesh, 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)
Purrception: Variational Flow Matching for Vector-Quantized Image Generation
by: Matişan, Răzvan-Andrei, et al.
Published: (2025)
by: Matişan, Răzvan-Andrei, et al.
Published: (2025)
Privately Learning Decision Lists and a Differentially Private Winnow
by: Bun, Mark, et al.
Published: (2026)
by: Bun, Mark, et al.
Published: (2026)
Private Prediction via Shrinkage
by: Yan, Chao
Published: (2026)
by: Yan, Chao
Published: (2026)
Private and Fair Machine Learning: Revisiting the Disparate Impact of Differentially Private SGD
by: Demelius, Lea, et al.
Published: (2025)
by: Demelius, Lea, et al.
Published: (2025)
Private Rate-Constrained Optimization with Applications to Fair Learning
by: Yaghini, Mohammad, et al.
Published: (2025)
by: Yaghini, Mohammad, et al.
Published: (2025)
Lower Bounds for Public-Private Learning under Distribution Shift
by: Setlur, Amrith, et al.
Published: (2025)
by: Setlur, Amrith, et al.
Published: (2025)
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
by: Tang, Xinyu, et al.
Published: (2023)
by: Tang, Xinyu, et al.
Published: (2023)
Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning
by: Gao, Fengyu, et al.
Published: (2024)
by: Gao, Fengyu, et al.
Published: (2024)
Continual Hyperbolic Learning of Instances and Classes
by: Ayoughi, Melika, et al.
Published: (2025)
by: Ayoughi, Melika, et al.
Published: (2025)
PoE-World: Compositional World Modeling with Products of Programmatic Experts
by: Piriyakulkij, Wasu Top, et al.
Published: (2025)
by: Piriyakulkij, Wasu Top, et al.
Published: (2025)
Private and Communication-Efficient Federated Learning based on Differentially Private Sketches
by: Zhang, Meifan, et al.
Published: (2024)
by: Zhang, Meifan, et al.
Published: (2024)
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)
BLIPs: Bayesian Learned Interatomic Potentials
by: Coscia, Dario, et al.
Published: (2025)
by: Coscia, Dario, et al.
Published: (2025)
PM-MOE: Mixture of Experts on Private Model Parameters for Personalized Federated Learning
by: Feng, Yu, et al.
Published: (2025)
by: Feng, Yu, et al.
Published: (2025)
How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization
by: Lowy, Andrew, et al.
Published: (2024)
by: Lowy, Andrew, et al.
Published: (2024)
Similar Items
-
Protect Your Score: Contact Tracing With Differential Privacy Guarantees
by: Romijnders, Rob, et al.
Published: (2023) -
DNA: Differentially private Neural Augmentation for contact tracing
by: Romijnders, Rob, et al.
Published: (2024) -
A Probabilistic Approach to Pose Synchronization for Multi-Reference Alignment with Applications to MIMO Wireless Communication Systems
by: Romijnders, Rob, et al.
Published: (2025) -
NoEsis: Differentially Private Knowledge Transfer in Modular LLM Adaptation
by: Romijnders, Rob, et al.
Published: (2025) -
Convex Approximation of Two-Layer ReLU Networks for Hidden State Differential Privacy
by: Romijnders, Rob, et al.
Published: (2024)