8 Practical Examples of Reinforcement Learning Even though we are still in the early stages of reinforcement learning, there are several applications and products that are starting to rely on the ...

The author presents a rapidly convergent algorithm to solve the general portfolio problem of maximizing concave utility functions subject to linear constraints. The algorithm is based on an iterative ...

A simple matrix formula is given for the observed information matrix when the EM algorithm is applied to categorical data with missing values. The formula requires only the design matrices, a matrix ...