4 citations · 11 across the 46 of their papers we have counts for
9 papers · 1 filter
Decentralized Linearized Consensus ADMM with Efficient Quantized Communication
Boyu Han, Xu Du, Karl H. Johansson +1
Distributed optimization offers significant advantages over centralized methods in terms of scalability and robustness when solving large-scale problems. In this paper, we propose…
CADMM-Prox: A Bi-level Consensus ADMM for Non-smooth Non-convex Distributed Consensus Optimization
Xu Du, Shuting Wu, Karl H. Johansson +1
Non-smooth and non-convex optimization problems are pervasive in machine learning, control, and signal processing, due to the need for sparse solutions and the inherently non-conve…
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…
Lightweight Real-Time ALADIN for Distributed Optimization
Yifei Wang, Xuhui Feng, Shimin Pan +3
This paper presents a real-time computational framework for multi-node distributed optimization by extending the Augmented Lagrangian Alternating Direction Inexact Newton (ALADIN)…
Mix-CALADIN: A Distributed Algorithm for Consensus Mixed-Integer Optimization
Boyu Han, Xu Du, Karl H. Johansson +1
This paper addresses distributed consensus optimization problems with mixed-integer variables, with a specific focus on Boolean variables. We introduce a novel distributed algorith…
Affine-coupled Distributed Optimization via Distributed Proximal Jacobian ADMM with Quantized Communication
Xu Du, Boyu Han, Ivano Notarnicola +2
This paper investigates distributed resource allocation optimization over directed graphs with limited communication bandwidth. We develop a novel distributed algorithm that integr…
Decentralized Optimization via RC-ALADIN with Efficient Quantized Communication
Xu Du, Karl H. Johansson, Apostolos I. Rikos
In this paper, we investigate the problem of decentralized consensus optimization over directed graphs with limited communication bandwidth. We introduce a novel decentralized opti…
Asynchronous Distributed Learning with Quantized Finite-Time Coordination
Nicola Bastianello, Apostolos I. Rikos, Karl H. Johansson
In this paper we address distributed learning problems over peer-to-peer networks. In particular, we focus on the challenges of quantized communications, asynchrony, and stochastic…
Asynchronous Distributed Optimization via ADMM with Efficient Communication
Apostolos I. Rikos, Wei Jiang, Themistoklis Charalambous +1
In this paper, we focus on an asynchronous distributed optimization problem. In our problem, each node is endowed with a convex local cost function, and is able to communicate with…