6 papers
Distributed and Decentralized Optimization Algorithms via Consensus ALADIN
Xu Du, Jingzhe Wang, Karl H. Johansson +1
Distributed optimization has found widespread applications in smart grids, optimal control, and machine learning. This paper studies distributed consensus optimization. We extend t…
Stability of Low-Rank Implicit Regularization in Perturbed Deep Matrix Factorization
Jingzhe Wang, Hung-Hsu Chou
This paper studies the stability of low-rank implicit regularization in deep matrix factorization, a tractable model for understanding how gradient-based training can favor low-com…
Distributed Consensus Optimization with Consensus ALADIN
Xu Du, Jingzhe Wang
TThe paper proposes the Consensus Augmented Lagrange Alternating Direction Inexact Newton (Consensus ALADIN) algorithm, a novel approach for solving distributed consensus optimizat…
A Time Splitting Based Optimization Method for Nonlinear MHE
Shuting Wu, Yifei Wang, Jingzhe Wang +2
Moving Horizon Estimation~(MHE) is essentially an optimization-based approach designed to estimate the states of dynamic systems within a moving time horizon. Traditional MHE solut…
A Bi-level Globalization Strategy for Non-convex Consensus ADMM and ALADIN
Xu Du, Jingzhe Wang, Xiaohua Zhou +1
In this paper, we formally analyze global convergence in the realm of distributed consensus optimization. Current solutions have explored such analysis, particularly focusing on co…
Consensus ALADIN: A Framework for Distributed Optimization and Its Application in Federated Learning
Xu Du, Jingzhe Wang
This paper investigates algorithms for solving distributed consensus optimization problems that are non-convex. Since Typical ALADIN (Typical Augmented Lagrangian based Alternating…