Algorithmic Learning in a Random World

Algorithmic Learning in a Random World describes recent theoretical and experimental developments in building computable approximations to Kolmogorov''s algorithmic notion of randomness. Based on these approximations, a new set of machine learning algorithms have been developed that can be used to make predictions and to estimate their confidence and credibility in high-dimensional spaces under th...