Predicting Structured Data

by Golchan Bakir, Thomas Hofmann (Editor), Alexander J. Smola (Editor)

State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.

Genres: Mathematics

361 pages, ebook

First published July 27, 2007

Reviews

[Michiel · Rating 3 out of 5]

Good book on structured output prediction. The introductory chapters and some of the latter ones gave some interesting and novel insights on kernel methods in general to me. I particularly liked the tutorial about energy models. Other chapters were somewhat too mathy and technical to bring their message across.

[Nick Black · Rating 4 out of 5]

A rigorous, comprehensive, succinct and even attractively-priced and -bound introduction to machine learning developments since 2000, with an informed focus on bioinformatic applications throughout. This fine job from MIT Press belongs on every researcher's bookshelf.