8 papers
Communication-Efficient Learning for Satellite Constellations
Ruxandra-Stefania Tudose, Moritz H. W. Grüss, Grace Ra Kim +2
Satellite constellations in low-Earth orbit are now widespread, enabling positioning, Earth imaging, and communications. In this paper we address the solution of learning problems…
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…
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…
Jointly Computation- and Communication-Efficient Distributed Learning
Xiaoxing Ren, Nicola Bastianello, Karl H. Johansson +1
We address distributed learning problems over undirected networks. Specifically, we focus on designing a novel ADMM-based algorithm that is jointly computation- and communication-e…
Personalized and Resilient Distributed Learning Through Opinion Dynamics
Luca Ballotta, Nicola Bastianello, Riccardo M. G. Ferrari +1
In this paper, we address two practical challenges of distributed learning in multi-agent network systems, namely personalization and resilience. Personalization is the need of het…