4 papers
Communication-Efficient Differentially Private Gradient Tracking for Distributed Optimization via Local Updates
Mihitha Maithripala, Chenyang Qiu, Zongli Lin
This paper studies privacy-preserving distributed optimization using gradient tracking with one communication-free local update between consecutive communication rounds. Since loca…
A Momentum-based Stochastic Algorithm for Linearly Constrained Nonconvex Optimization
Chenyang Qiu, Mihitha Maithripala, Zongli Lin
This paper studies a stochastic algorithm for linearly constrained nonconvex optimization, where the objective function is smooth but only unbiased stochastic gradients with bounde…
Privacy-Preserving Dynamic Average Consensus by Masking Reference Signals
Mihitha Maithripala, Zongli Lin
In multi-agent systems, dynamic average consensus (DAC) is a decentralized estimation strategy in which a set of agents tracks the average of time-varying reference signals. Becaus…
Privacy-Preserving Distributed Control for a Networked Battery Energy Storage System
Mihitha Maithripala, Zongli Lin
The increasing deployment of distributed Battery Energy Storage Systems (BESSs) in modern power grids necessitates effective coordination strategies to ensure state-of-charge (SoC)…