Algorithmic Learning in a Random World

by Vladimir Vovk, Alex Gammerman (Contributor), Glenn Shafer (Contributor)

A new scientific monograph developing significant new algorithmic foundations in machine learning theory. Researchers and postgraduates in CS, statistics, and A.I. will find the book an authoritative and formal presentation of some of the most promising theoretical developments in machine learning.

340 pages, Paperback

First published January 1, 2005