16 papers
Resilient Consensus-Based Target Tracking under False Data Injection Attacks in Multi-Agent Networks
Amir Ahmad Ghods, Mohammadreza Doostmohammadian
Distributed target tracking in multi-agent networks plays a critical role in cooperative sensing and autonomous navigation. However, it faces significant challenges in highly dynam…
Using Non-Lipschitz Signum-based Functions for Distributed Optimization and Machine Learning: Trade-off Between Con-vergence Rate and Optimality Gap
Mohammadreza Doostmohammadian, Amir Ahmad Ghods, Alireza Aghasi +2
In recent years, the prevalence of large-scale data-sets and the demand for sophisti-cated learning models have necessitated the development of efficient distributed ma-chine learn…
Distributed Observer-based Fault Detection over Intelligent Networked Multi-Vehicle Systems
Mohammadreza Doostmohammadian, Hamid R. Rabiee
Decentralized strategies are of interest for local decision-making over multi-vehicle networks. This paper studies mixed traffic networks of human-driven and autonomous vehicles wi…
Impact of Clustering on the Observability and Controllability of Complex Networks
Mohammadreza Doostmohammadian, Hamid R. Rabiee
The increasing complexity and interconnectedness of systems across various fields have led to a growing interest in studying complex networks, particularly Scale-Free (SF) networks…
Machine Learning and CPU (Central Processing Unit) Scheduling Co-Optimization over a Network of Computing Centers
Mohammadreza Doostmohammadian, Zulfiya R. Gabidullina, Hamid R. Rabiee
In the rapidly evolving research on artificial intelligence (AI) the demand for fast, computationally efficient, and scalable solutions has increased in recent years. The problem o…
Distributed Allocation and Resource Scheduling Algorithms Resilient to Link Failure
Mohammadreza Doostmohammadian, Sergio Pequito
Distributed resource allocation (DRA) is fundamental to modern networked systems, spanning applications from economic dispatch in smart grids to CPU scheduling in data centers. Con…