Submodular function optimisation has emerged as a cornerstone of contemporary algorithm design, offering a powerful framework to address a broad range of combinatorial problems characterised by the ...

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 ...

This paper presents three algorithms for solving linear programming problems in which some or all of the objective function coefficients are specified in terms of intervals. Which algorithm is ...

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 ...

SHENZHEN, China, May 2, 2025 /PRNewswire/ -- MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO) announced today the launch of their latest classifier auto-optimization technology based on ...