Understanding machine learning on graphs

Of the branches of artificial intelligence, machine learning is one that has attracted the most attention in recent years. It refers to a class of computer algorithms that automatically learn and improve their skills through experience without being explicitly programmed. Such an approach takes inspiration from nature. Imagine an athlete who faces a novel movement for the first time: they start slowly, carefully imitating the gesture of a coach, trying, making mistakes, and trying again. Eventually, they will improve, becoming more and more confident.

Now, how does this concept translate to machines? It is essentially an optimization problem. The goal is to find a mathematical model that is able to achieve the best possible performance on a particular task. Performance can be measured using a specific performance metric (also known as a loss function or cost function). In a common learning task, the algorithm is provided with data, possibly...