13 citations · 16 across the 23 of their papers we have counts for
9 papers · 1 filter
A Global Convergence Analysis of Consensus ALADIN for Convex Optimization
Xu Du, Shuting Wu, Karl H. Johansson +1
Distributed optimization problems are pervasive in machine learning and optimal control. In this paper, we study smooth strongly convex distributed consensus optimization problems.…
Distributed Optimization with Nesterov Momentum and Finite-Time Quantized Averaging over Directed Networks: Extended Version
Ruochen Wu, Xu Du, Karl H. Johansson +2
In modern large-scale networked systems, rapidly solving optimization problems while utilizing communication resources efficiently is critical for addressing complex tasks. However…
Distributed Coordination Algorithms with Efficient Communication for Open Multi-Agent Systems with Dynamic Communication Links and Processing Delays: Extended Version
Jiaqi Hu, Karl H. Johansson, Apostolos I. Rikos
In this paper we focus on the distributed quantized average consensus problem in open multi-agent systems consisting of dynamic directed communication links among active nodes. We…
Distributed Quantized Average Consensus in Open Multi-Agent Systems with Dynamic Communication Links
Jiaqi Hu, Karl H. Johansson, Apostolos I. Rikos
In this paper, we focus on the distributed quantized average consensus problem in open multi-agent systems consisting of communication links that change dynamically over time. Open…
Distributed Optimization and Learning for Automated Stepsize Selection with Finite Time Coordination
Apostolos I. Rikos, Nicola Bastianello, Themistoklis Charalambous +1
Distributed optimization and learning algorithms are designed to operate over large scale networks enabling processing of vast amounts of data effectively and efficiently. One of t…
Distributed Optimization with Efficient Communication, Event-Triggered Solution Enhancement, and Operation Stopping
Apostolos I. Rikos, Wei Jiang, Themistoklis Charalambous +1
In modern large-scale systems with sensor networks and IoT devices it is essential to collaboratively solve complex problems while utilizing network resources efficiently. In our p…
Distributed Optimization with Finite Bit Adaptive Quantization for Efficient Communication and Precision Enhancement
Apostolos I. Rikos, Wei Jiang, Themistoklis Charalambous +1
In realistic distributed optimization scenarios, individual nodes possess only partial information and communicate over bandwidth constrained channels. For this reason, the develop…
Distributed Optimization via Gradient Descent with Event-Triggered Zooming over Quantized Communication
Apostolos I. Rikos, Wei Jiang, Themistoklis Charalambous +1
In this paper, we study unconstrained distributed optimization strongly convex problems, in which the exchange of information in the network is captured by a directed graph topolog…
Distributed Optimization with Quantized Gradient Descent
Apostolos I. Rikos, Wei Jiang, Themistoklis Charalambous +1
In this paper, we consider the unconstrained distributed optimization problem, in which the exchange of information in the network is captured by a directed graph topology, thus, n…