Regularization is a technique used in machine learning to prevent overfitting, which is a situation where a machine learning model performs well on training data but poorly on unseen data (test data).

Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test accuracy is very low, the model highly overfits the training dataset ...

We investigate a class of reinforcement learning dynamics where players adjust their strategies based on their actions' cumulative payoffs over time—specifically, by playing mixed strategies that ...