In the lower part of the figure, it can be seen that L2O leverages on a set of training problem instances from the target optimization problem class to gain knowledge. This knowledge can help identify ...

Researchers have developed a new, data-driven machine-learning technique that speeds up software programs used to solve complex optimization problems that can have millions of potential solutions.

In a new paper in Science Advances, researchers at JPMorgan Chase, the U.S. Department of Energy's (DOE) Argonne National Laboratory and Quantinuum have demonstrated clear evidence of a quantum ...

This seminar is part of the Research Semester Programma 'Democratizing real-world problem tailored optimization '.

Dr. James McCaffrey of Microsoft Research says that when quantum computing becomes generally available, evolutionary algorithms for training huge neural networks could become a very important and ...

Dr. James McCaffrey of Microsoft Research uses full code samples to detail an evolutionary algorithm technique that apparently hasn't been published before. The goal of a combinatorial optimization ...

When people program new deep learning AI models — those that can focus on the right features of data by themselves — the vast majority rely on optimization algorithms, or optimizers, to ensure the ...