Differentially Private Optimization for Non-Decomposable Objective Functions
Fuente:
arXiv
Saved in:
| Main Authors: | Kong, Weiwei, Medina, Andrés Muñoz, Ribero, Mónica |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Sequentially Auditing Differential Privacy
by: González, Tomás, et al.
Published: (2025)
by: González, Tomás, et al.
Published: (2025)
Improving the Privacy and Practicality of Objective Perturbation for Differentially Private Linear Learners
by: Redberg, Rachel, et al.
Published: (2023)
by: Redberg, Rachel, et al.
Published: (2023)
Differentially Private Release and Learning of Threshold Functions
by: Bun, Mark, et al.
Published: (2015)
by: Bun, Mark, et al.
Published: (2015)
Differentially Private Synthetic Data Release for Topics API Outputs
by: Dick, Travis, et al.
Published: (2025)
by: Dick, Travis, 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)
Differentially Private Bilevel Optimization
by: Kornowski, Guy
Published: (2024)
by: Kornowski, Guy
Published: (2024)
Output Perturbation for Differentially Private Convex Optimization: Faster and More General
by: Lowy, Andrew, et al.
Published: (2021)
by: Lowy, Andrew, et al.
Published: (2021)
ContinuousBench: Can Differentially Private Synthetic Text Improve Capabilities?
by: Liu, Peihan, et al.
Published: (2026)
by: Liu, Peihan, et al.
Published: (2026)
Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates
by: Menart, Michael, et al.
Published: (2023)
by: Menart, Michael, et al.
Published: (2023)
Differentially Private Attention Computation
by: Gao, Yeqi, et al.
Published: (2023)
by: Gao, Yeqi, et al.
Published: (2023)
Delving into Differentially Private Transformer
by: Ding, Youlong, et al.
Published: (2024)
by: Ding, Youlong, et al.
Published: (2024)
Differentially Private Diffusion Models
by: Dockhorn, Tim, et al.
Published: (2022)
by: Dockhorn, Tim, et al.
Published: (2022)
DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction
by: Zhang, Xinwei, et al.
Published: (2024)
by: Zhang, Xinwei, et al.
Published: (2024)
DOPPLER: Differentially Private Optimizers with Low-pass Filter for Privacy Noise Reduction
by: Zhang, Xinwei, et al.
Published: (2024)
by: Zhang, Xinwei, et al.
Published: (2024)
Clustering and Median Aggregation Improve Differentially Private Inference
by: Amin, Kareem, et al.
Published: (2025)
by: Amin, Kareem, 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 and Communication-Efficient Federated Learning based on Differentially Private Sketches
by: Zhang, Meifan, et al.
Published: (2024)
by: Zhang, Meifan, et al.
Published: (2024)
Optimal Rates for Pure $\varepsilon$-Differentially Private Stochastic Convex Optimization with Heavy Tails
by: Lowy, Andrew
Published: (2026)
by: Lowy, Andrew
Published: (2026)
Differentially Private Conditional Independence Testing
by: Kalemaj, Iden, et al.
Published: (2023)
by: Kalemaj, Iden, et al.
Published: (2023)
Differentially Private Random Feature Model
by: Liao, Chunyang, et al.
Published: (2024)
by: Liao, Chunyang, et al.
Published: (2024)
Differentially Private Log-Location-Scale Regression Using Functional Mechanism
by: Sheng, Jiewen, et al.
Published: (2024)
by: Sheng, Jiewen, et al.
Published: (2024)
Enabling Differentially Private Federated Learning for Speech Recognition: Benchmarks, Adaptive Optimizers and Gradient Clipping
by: Pelikan, Martin, et al.
Published: (2023)
by: Pelikan, Martin, et al.
Published: (2023)
Differentially Private Domain Adaptation with Theoretical Guarantees
by: Bassily, Raef, et al.
Published: (2023)
by: Bassily, Raef, et al.
Published: (2023)
Practical Differentially Private Hyperparameter Tuning with Subsampling
by: Koskela, Antti, et al.
Published: (2023)
by: Koskela, Antti, et al.
Published: (2023)
Scaling Laws for Differentially Private Language Models
by: McKenna, Ryan, et al.
Published: (2025)
by: McKenna, Ryan, et al.
Published: (2025)
Differentially Private Learners for Heterogeneous Treatment Effects
by: Schröder, Maresa, et al.
Published: (2025)
by: Schröder, Maresa, et al.
Published: (2025)
Differentially Private Training of Mixture of Experts Models
by: Tholoniat, Pierre, et al.
Published: (2024)
by: Tholoniat, Pierre, et al.
Published: (2024)
Revisiting Differentially Private Hyper-parameter Tuning
by: Xiang, Zihang, et al.
Published: (2024)
by: Xiang, Zihang, et al.
Published: (2024)
Correlated Noise Mechanisms for Differentially Private Learning
by: Pillutla, Krishna, et al.
Published: (2025)
by: Pillutla, Krishna, et al.
Published: (2025)
Differentially Private Decentralized Learning with Random Walks
by: Cyffers, Edwige, et al.
Published: (2024)
by: Cyffers, Edwige, et al.
Published: (2024)
Noise-Aware Differentially Private Variational Inference
by: Alrawajfeh, Talal, et al.
Published: (2024)
by: Alrawajfeh, Talal, et al.
Published: (2024)
Privacy of the last iterate in cyclically-sampled DP-SGD on nonconvex composite losses
by: Kong, Weiwei, et al.
Published: (2024)
by: Kong, Weiwei, et al.
Published: (2024)
PLRV-O: Advancing Differentially Private Deep Learning via Privacy Loss Random Variable Optimization
by: Yang, Qin, et al.
Published: (2025)
by: Yang, Qin, et al.
Published: (2025)
Privately Counting Partially Ordered Data
by: Joseph, Matthew, et al.
Published: (2024)
by: Joseph, Matthew, et al.
Published: (2024)
Differentially Private Inference for Longitudinal Linear Regression
by: Sopa, Getoar, et al.
Published: (2026)
by: Sopa, Getoar, et al.
Published: (2026)
Differentially Private E-Values
by: Csillag, Daniel, et al.
Published: (2025)
by: Csillag, Daniel, et al.
Published: (2025)
Differentially Private Learned Indexes
by: Du, Jianzhang, et al.
Published: (2024)
by: Du, Jianzhang, et al.
Published: (2024)
S-BDT: Distributed Differentially Private Boosted Decision Trees
by: Peinemann, Thorsten, et al.
Published: (2023)
by: Peinemann, Thorsten, et al.
Published: (2023)
DP-LDMs: Differentially Private Latent Diffusion Models
by: Liu, Michael F., et al.
Published: (2023)
by: Liu, Michael F., et al.
Published: (2023)
Oracle-Efficient Differentially Private Learning with Public Data
by: Block, Adam, et al.
Published: (2024)
by: Block, Adam, et al.
Published: (2024)
Similar Items
-
Sequentially Auditing Differential Privacy
by: González, Tomás, et al.
Published: (2025) -
Improving the Privacy and Practicality of Objective Perturbation for Differentially Private Linear Learners
by: Redberg, Rachel, et al.
Published: (2023) -
Differentially Private Release and Learning of Threshold Functions
by: Bun, Mark, et al.
Published: (2015) -
Differentially Private Synthetic Data Release for Topics API Outputs
by: Dick, Travis, 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)