[Kory] has been writing genetic algorithms for a few months now. This in itself isn’t anything unique or exceptional, except for what he’s getting these genetic algorithms to do. [Kory]… ...

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 ...

This paper describes an algorithm for maximising a conditional likelihood function when the corresponding unconditional likelihood function is more easily maximised. The algorithm is similar to the EM ...

We present an implementable algorithm for solving constrained optmization problems defined by functions that are not everywhere differentiable. The method is based on combining, modifying and ...

Submodular Function Optimization and Algorithms Publication Trend The graph below shows the total number of publications each year in Submodular Function Optimization and Algorithms.

Researchers have developed a new AI-powered algorithm to help understand how different cells organize themselves into particular tissues and communicate with one another.

Trigonometric functions are often used in embedded systems. Motor drivecontrol applications such as the Park Transform, Clarke Transform, andPWMgeneration use trigonometric functions extensively.

The new algorithm discusses a method of ranking web pages called, Groupwise Scoring Functions. Without confirmation from Google we cannot know for certain if it is in use.