Private and Federated Stochastic Convex Optimization: Efficient Strategies for Centralized Systems
Fuente:
arXiv
Saved in:
| Main Authors: | Reshef, Roie, Levy, Kfir Y. |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Privacy-Preserving Federated Convex Optimization: Balancing Partial-Participation and Efficiency via Noise Cancellation
by: Reshef, Roie, et al.
Published: (2025)
by: Reshef, Roie, et al.
Published: (2025)
Bringing Order to Asynchronous SGD: Towards Optimality under Data-Dependent Delays with Momentum
by: Dahan, Tehila, et al.
Published: (2026)
by: Dahan, Tehila, et al.
Published: (2026)
Local MixVR: Breaking the Communication-Sample Dependence in Distributed Learning
by: Dahan, Tehila, et al.
Published: (2026)
by: Dahan, Tehila, et al.
Published: (2026)
Enhancing Parallelism in Decentralized Stochastic Convex Optimization
by: Eisen, Ofri, et al.
Published: (2025)
by: Eisen, Ofri, et al.
Published: (2025)
SLowcal-SGD: Slow Query Points Improve Local-SGD for Stochastic Convex Optimization
by: Dahan, Tehila, et al.
Published: (2023)
by: Dahan, Tehila, et al.
Published: (2023)
$μ^2$-SGD: Stable Stochastic Optimization via a Double Momentum Mechanism
by: Dahan, Tehila, et al.
Published: (2023)
by: Dahan, Tehila, et al.
Published: (2023)
Fault Tolerant ML: Efficient Meta-Aggregation and Synchronous Training
by: Dahan, Tehila, et al.
Published: (2024)
by: Dahan, Tehila, et al.
Published: (2024)
Weight for Robustness: A Comprehensive Approach towards Optimal Fault-Tolerant Asynchronous ML
by: Dahan, Tehila, et al.
Published: (2025)
by: Dahan, Tehila, et al.
Published: (2025)
Second-Order Convergence in Private Stochastic Non-Convex Optimization
by: Tao, Youming, et al.
Published: (2025)
by: Tao, Youming, et al.
Published: (2025)
Safety in the Face of Adversity: Achieving Zero Constraint Violation in Online Learning with Slowly Changing Constraints
by: Hamoud, Bassel, et al.
Published: (2025)
by: Hamoud, Bassel, et al.
Published: (2025)
Faster Algorithms for User-Level Private Stochastic Convex Optimization
by: Lowy, Andrew, et al.
Published: (2024)
by: Lowy, Andrew, et al.
Published: (2024)
Beyond Communication Overhead: A Multilevel Monte Carlo Approach for Mitigating Compression Bias in Distributed Learning
by: Zukerman, Ze'ev, et al.
Published: (2025)
by: Zukerman, Ze'ev, et al.
Published: (2025)
Optimal Rates for Pure $\varepsilon$-Differentially Private Stochastic Convex Optimization with Heavy Tails
by: Lowy, Andrew
Published: (2026)
by: Lowy, Andrew
Published: (2026)
Dynamic Byzantine-Robust Learning: Adapting to Switching Byzantine Workers
by: Dorfman, Ron, et al.
Published: (2024)
by: Dorfman, Ron, et al.
Published: (2024)
Gradient-Variation Online Adaptivity for Accelerated Optimization with Hölder Smoothness
by: Zhao, Yuheng, et al.
Published: (2025)
by: Zhao, Yuheng, et al.
Published: (2025)
Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions
by: Asi, Hilal, et al.
Published: (2024)
by: Asi, Hilal, et al.
Published: (2024)
On Traceability in $\ell_p$ Stochastic Convex Optimization
by: Voitovych, Sasha, et al.
Published: (2025)
by: Voitovych, Sasha, et al.
Published: (2025)
DE-PADA: Personalized Augmentation and Domain Adaptation for ECG Biometrics Across Physiological States
by: Saleh, Amro Abu, et al.
Published: (2025)
by: Saleh, Amro Abu, et al.
Published: (2025)
Prediction-Powered Semi-Supervised Learning with Online Power Tuning
by: Shoham, Noa, et al.
Published: (2025)
by: Shoham, Noa, et al.
Published: (2025)
The Price of Adaptivity in Stochastic Convex Optimization
by: Carmon, Yair, et al.
Published: (2024)
by: Carmon, Yair, et al.
Published: (2024)
Stochastic Difference-of-Convex Optimization with Momentum
by: Chayti, El Mahdi, et al.
Published: (2025)
by: Chayti, El Mahdi, et al.
Published: (2025)
Optimal Rates for Robust Stochastic Convex Optimization
by: Gao, Changyu, et al.
Published: (2024)
by: Gao, Changyu, et al.
Published: (2024)
Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization
by: Attias, Idan, et al.
Published: (2024)
by: Attias, Idan, et al.
Published: (2024)
Flat Minima and Generalization: Insights from Stochastic Convex Optimization
by: Schliserman, Matan, et al.
Published: (2025)
by: Schliserman, Matan, et al.
Published: (2025)
Convex Distillation: Efficient Compression of Deep Networks via Convex Optimization
by: Varshney, Prateek, et al.
Published: (2024)
by: Varshney, Prateek, et al.
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)
Bring Your Own (Non-Robust) Algorithm to Solve Robust MDPs by Estimating The Worst Kernel
by: Wang, Kaixin, et al.
Published: (2023)
by: Wang, Kaixin, et al.
Published: (2023)
Stochastic Weakly Convex Optimization Beyond Lipschitz Continuity
by: Gao, Wenzhi, et al.
Published: (2024)
by: Gao, Wenzhi, et al.
Published: (2024)
The Sample Complexity of Gradient Descent in Stochastic Convex Optimization
by: Livni, Roi
Published: (2024)
by: Livni, Roi
Published: (2024)
Online Non-Stationary Stochastic Quasar-Convex Optimization
by: Pun, Yuen-Man, et al.
Published: (2024)
by: Pun, Yuen-Man, et al.
Published: (2024)
The Sample Complexity of Parameter-Free Stochastic Convex Optimization
by: Lawrence, Jared, et al.
Published: (2025)
by: Lawrence, Jared, et al.
Published: (2025)
Stochastic Non-Smooth Convex Optimization with Unbounded Gradients
by: Kovalev, Dmitry
Published: (2026)
by: Kovalev, Dmitry
Published: (2026)
Boundary on the Table: Efficient Black-Box Decision-Based Attacks for Structured Data
by: Kazoom, Roie, et al.
Published: (2025)
by: Kazoom, Roie, et al.
Published: (2025)
Rapid Overfitting of Multi-Pass Stochastic Gradient Descent in Stochastic Convex Optimization
by: Vansover-Hager, Shira, et al.
Published: (2025)
by: Vansover-Hager, Shira, 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)
Bayesian Optimization for Non-Convex Two-Stage Stochastic Optimization Problems
by: Buckingham, Jack M., et al.
Published: (2024)
by: Buckingham, Jack M., et al.
Published: (2024)
DP-FedAdamW: An Efficient Optimizer for Differentially Private Federated Large Models
by: Liu, Jin, et al.
Published: (2026)
by: Liu, Jin, et al.
Published: (2026)
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)
PrivEraserVerify: Efficient, Private, and Verifiable Federated Unlearning
by: Goswami, Parthaw, et al.
Published: (2026)
by: Goswami, Parthaw, et al.
Published: (2026)
Fast Rates in Stochastic Online Convex Optimization by Exploiting the Curvature of Feasible Sets
by: Tsuchiya, Taira, et al.
Published: (2024)
by: Tsuchiya, Taira, et al.
Published: (2024)
Similar Items
-
Privacy-Preserving Federated Convex Optimization: Balancing Partial-Participation and Efficiency via Noise Cancellation
by: Reshef, Roie, et al.
Published: (2025) -
Bringing Order to Asynchronous SGD: Towards Optimality under Data-Dependent Delays with Momentum
by: Dahan, Tehila, et al.
Published: (2026) -
Local MixVR: Breaking the Communication-Sample Dependence in Distributed Learning
by: Dahan, Tehila, et al.
Published: (2026) -
Enhancing Parallelism in Decentralized Stochastic Convex Optimization
by: Eisen, Ofri, et al.
Published: (2025) -
SLowcal-SGD: Slow Query Points Improve Local-SGD for Stochastic Convex Optimization
by: Dahan, Tehila, et al.
Published: (2023)