Proximal gradient methods for learning

Proximal gradient methods are algorithms that are used to help things learn. It's like a teacher in a classroom – the teacher will tell the students what they need to do to learn something new. Proximal gradient methods work similarly: they give computers instructions on how to learn a new system or process. Basically, it is a mathematical way of telling the computer what steps to take to learn something. For example, if the computer needs to learn how to recognize a certain object in an image, the proximal gradient method will tell the computer which steps to take to get there. In the end, the computer will be able to recognize the object in the image.