Solving complex optimization problems is central to many modern technologies, from logistics and financial modeling to chip ...

Are you passionate about developing AI-based and quantum-inspired solutions for the next generation of sustainable energy systems? We are now looking for a fully funded Doctoral Researcher to work on ...

Arbor separates strategy from execution using isolated git worktrees, so engineering teams can finally trace which optimization actually moved the needle.

Abstract: Over the last three decades, a large number of evolutionary algorithms have been developed for solving multi-objective optimization problems. However, there lacks an upto-date and ...

50+ multitask evolutionary algorithms for multitask optimization 50+ single-task evolutionary algorithms that can handle multitask optimization problems 200+ multitask optimization problem cases with ...

Python and MATLAB are valuable for an electrical engineer's career, but the better choice depends on your field, industry, and career goals. Electrical engineers face many challenges: dealing with ...

Growing data center power demands are driving server end-equipment manufacturers to reach higher power-conversion efficiencies in order to reduce the thermal footprint of their systems. The transition ...

In this project it is used a Machine Learning model based on a method called Extreme Learning, with the employment of L2-regularization. In particular, a comparison was carried out between: (A1) which ...

A common use case for high-level synthesis (HLS) is taking 3rd party generated or legacy C/C++ algorithms and converting the algorithm to a hardware implementation using an HLS compiler. This can ...