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 ...

Knowing when to hold 'em, and when to fold 'em is one of life's perpetual mysteries. If you have a mathematical inclination, or a bent for probabilities, this book might well catalyze a turning point ...

Dr. James McCaffrey of Microsoft Research says that when quantum computing becomes generally available, evolutionary algorithms for training huge neural networks could become a very important and ...

At the core of reinforcement learning is the concept that the optimal behavior or action is reinforced by a positive reward. Similar to toddlers learning how to walk who adjust actions based on the ...

Taking inspiration from the way humans seem to learn, scientists have created AI software capable of picking up new knowledge in a far more efficient and sophisticated way. Fig. 1. People can learn ...

Categorizing and representing huge amounts of data -- we're talking about peta- or even exabytes of information -- synthetically is a challenge of the future. A research paper proposes an efficient ...

Researchers planning mating experiments are faced with a critical design choice—deciding how many pairs and which pairs of individuals to mate. The number of crosses in a mating experiment can ...