Image de couverture de livre

Local Differential Privacy for Distributed Stochastic Aggregative Optimization with Guaranteed Optimality

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Chen, Ziqin, Wang, Yongqiang
Format:	Preprint
Publié:	2025
Sujets:	Systems and Control
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Locally Differentially Private Distributed Online Learning with Guaranteed Optimality
par: Chen, Ziqin, et autres
Publié: (2023)

Distributed Finite-Horizon Optimal Control for Consensus with Differential Privacy Guarantees
par: Ma, Yuwen, et autres
Publié: (2025)

Robust Constrained Consensus and Inequality-constrained Distributed Optimization with Guaranteed Differential Privacy and Accurate Convergence
par: Wang, Yongqiang, et autres
Publié: (2024)

Accelerating Optimization and Machine Learning through Decentralization
par: Chen, Ziqin, et autres
Publié: (2026)

Ensuring Truthfulness in Distributed Aggregative Optimization
par: Chen, Ziqin, et autres
Publié: (2025)

Local Updates in Distributed Optimization: Provable Acceleration and Topology Effects
par: Wang, Zuang, et autres
Publié: (2026)

Privacy in Multi-agent Systems
par: Wang, Yongqiang
Publié: (2024)

Distributed Least-Squares Optimization Solvers with Differential Privacy
par: Liu, Weijia, et autres
Publié: (2024)

Differentially Private Distributed Nonconvex Stochastic Optimization with Quantized Communication
par: Chen, Jialong, et autres
Publié: (2024)

Privacy-Preserving Distributed Stochastic Optimization with Homomorphic Encryption and Heterogeneous Stepsizes
par: Zhou, Haoqiang, et autres
Publié: (2026)

Differential Privacy in Nonlinear Dynamical Systems with Tracking Performance Guarantees
par: Chowdhury, Dhrubajit, et autres
Publié: (2024)

Differentially Private Gradient-Tracking-Based Distributed Stochastic Optimization over Directed Graphs
par: Chen, Jialong, et autres
Publié: (2025)

Scenario Reduction with Guarantees for Stochastic Optimal Control of Linear Systems
par: Cordiano, Francesco, et autres
Publié: (2024)

Differentially Private Distributed Stochastic Optimization with Time-Varying Sample Sizes
par: Wang, Jimin, et autres
Publié: (2023)

Can Inherent Communication Noise Guarantee Privacy in Distributed Cooperative Control ?
par: Ma, Yuwen, et autres
Publié: (2026)

Optimal Privacy-Aware Stochastic Sampling
par: Weng, Chuanghong, et autres
Publié: (2024)

On Linear Convergence of Distributed Stochastic Bilevel Optimization over Undirected Networks via Gradient Aggregation
par: Tak, Ajay, et autres
Publié: (2025)

Guaranteeing Both Consensus and Optimality in Decentralized Nonconvex Optimization with Multiple Local Updates
par: Liu, Jie, et autres
Publié: (2025)

Density-Driven Optimal Control: Convergence Guarantees for Stochastic LTI Multi-Agent Systems
par: Lee, Kooktae
Publié: (2026)

Differentially-Private Distributed Model Predictive Control of Linear Discrete-Time Systems with Global Constraints
par: Zhang, Kaixiang, et autres
Publié: (2024)

Learning a Contracting KKL-observer with Local Optimal Guarantees
par: Galimberti, Clara Lucía, et autres
Publié: (2026)

Privacy-Preserving Distributed Optimization and Learning
par: Chen, Ziqin, et autres
Publié: (2024)

Scalable Distributed Reproduction Numbers of Network Epidemics with Differential Privacy
par: Chen, Bo, et autres
Publié: (2025)

Gradient Manipulation in Distributed Stochastic Gradient Descent with Strategic Agents: Truthful Incentives with Convergence Guarantees
par: Chen, Ziqin, et autres
Publié: (2026)

PAC Finite-Time Safety Guarantees for Stochastic Systems with Unknown Disturbance Distributions
par: Wu, Taoran, et autres
Publié: (2026)

Passivity-Based Local Design Conditions for Global Optimality in Distributed Convex Optimization
par: Jane-Soneira, Pol, et autres
Publié: (2025)

Stochastic Optimal Control via Local Occupation Measures
par: Holtorf, Flemming, et autres
Publié: (2022)

Nonconvex Distributed Feedback Optimization for Aggregative Cooperative Robotics
par: Carnevale, Guido, et autres
Publié: (2023)

Towards Optimality Preserving Aggregation for Scheduling Distributed Energy Resources
par: Appino, Riccardo Remo, et autres
Publié: (2019)

Distributed Truncated Predictive Control for Networked Systems under Uncertainty: Stability and Near-Optimality Guarantee
par: Xu, Eric, et autres
Publié: (2023)

Guaranteed Privacy-Preserving $\mathcal{H}_{\infty}$-Optimal Interval Observer Design for Bounded-Error LTI Systems
par: Khajenejad, Mohammad, et autres
Publié: (2023)

Feedforward Density-Driven Optimal Control for Tracking Time-Varying Distributions with Guaranteed Stability
par: Martinez, Julian, et autres
Publié: (2026)

Synthesizing Grid Data with Cyber Resilience and Privacy Guarantees
par: Wu, Shengyang, et autres
Publié: (2025)

Privacy-Preserving Nonlinear Cloud-based Model Predictive Control via Affine Masking
par: Zhang, Kaixiang, et autres
Publié: (2021)

Ensure Differential Privacy and Convergence Accuracy in Consensus Tracking and Aggregative Games with Coupling Constraints
par: Wang, Yongqiang
Publié: (2022)

Data-Driven Distributed Optimization via Aggregative Tracking and Deep-Learning
par: Brumali, Riccardo, et autres
Publié: (2025)

Learning to Pursue AC Optimal Power Flow Solutions with Feasibility Guarantees
par: Ajeyemi, Damola, et autres
Publié: (2025)

Stochastic Differential Dynamic Programming for Trajectory Optimization under Partial Observability
par: Fujiwara, Masahiro, et autres
Publié: (2026)

Stochastic MPC with Online-optimized Policies and Closed-loop Guarantees
par: Bartos, Marcell, et autres
Publié: (2025)

Optimal Sequencing and Motion Control in a Roundabout with Safety Guarantees
par: Chen, Yingqing, et autres
Publié: (2024)