Distributed algorithms for graph problems represent a vibrant area of study that addresses the challenges of decentralised computation across interconnected networks. By partitioning complex graph ...

Adaptive algorithms have emerged as a cornerstone in the development of networked systems, providing robust methods for real‐time estimation, classification and signal processing over distributed ...

An integrated intent-driven verification and distributed monitoring framework strengthens network infrastructure security by uniting real-time ...

In recent years, distributed multi-agent systems (MAS) have gained significant attention across robotics, autonomous vehicles ...

Welcome to the latest edition of “Quantum Leap” where The Fly decodes news and activity in the quantum computing space. CNSA COMPLIANCE: Sealsq ...

Basic principles behind distributed systems (collections of independent components that appear to users as a single coherent system) and main paradigms used to organize them. This course satisfies the ...

“Abstract—Large-scale distributed deep learning training has enabled developments of more complex deep neural network models to learn from larger datasets for sophisticated tasks. In particular, ...

Retail data platforms sit at the center of how modern retail runs. Shopper expectations have moved to immediate availability ...

Computers are all around us. How does this affect the world we live in? This course is a broad introduction to computing technology for humanities and social science students. Topics will be drawn ...