Algorithmic learning in a random world

This scientific monograph develops significant new algorithmic foundations in machine learning theory. Researchers and postgraduates in CS, statistics, and A.I. should find the book an authoritative and formal presentation of some of the most promising theoretical developments in machine learning. Introduction; Conformal prediction; Classification with conformal predictors; Modifications of conformal predictors; Probabilistic prediction I: impossibility results; Probabilistic prediction II: Venn predictors; Beyond exchangeability; On-line compression modeling I: conformal prediction; On-line compression modeling II: Venn prediction; Perspectives and contrasts