Predicting Structured Data (Neural Information Processing series)

Gokhan H. Bakir; Thomas Hofmann; Bernhard Scholkopf; Alexander J. Smola; Ben Taskar; S. V. N. Vishwanathan

ISBN 10: 0262026171 / ISBN 13: 9780262026178

Published by The MIT Press, Cambridge, MA, 2007

About this Item

First edition, the uncommon issue in full cloth and dust jacket. Pale green cloth covered boards with gilt titles to spine, neat two words "Seung Lab" to front pastedown, no other markings. Publisher's illustrated dust jacket with a 1 inch long closed tear to rear panel and a shorter closed tear to head of spine, minor edgewear, now covered in protective mylar jacket protector. Uncommon in hardcover. Seller Inventory # 003177

Bibliographic Details

Title: Predicting Structured Data (Neural ...

Publisher: The MIT Press, Cambridge, MA

Publication Date: 2007

Binding: Hardcover

Condition: Fine

Dust Jacket Condition: Near Fine

Edition: 1st Edition

About this title

Synopsis:

Machine learning develops intelligent computer systems that are able to generalize from previously seen examples. A new domain of machine learning, in which the prediction must satisfy the additional constraints found in structured data, poses one of machine learning's greatest challenges: learning functional dependencies between arbitrary input and output domains. This volume presents and analyzes the state of the art in machine learning algorithms and theory in this novel field. The contributors discuss applications as diverse as machine translation, document markup, computational biology, and information extraction, among others, providing a timely overview of an exciting field.

Contributors Yasemin Altun, Gökhan Bakir, Olivier Bousquet, Sumit Chopra, Corinna Cortes, Hal Daumé III, Ofer Dekel, Zoubin Ghahramani, Raia Hadsell, Thomas Hofmann, Fu Jie Huang, Yann LeCun, Tobias Mann, Daniel Marcu, David McAllester, Mehryar Mohri, William Stafford Noble, Fernando Pérez-Cruz, Massimiliano Pontil, Marc'Aurelio Ranzato, Juho Rousu, Craig Saunders, Bernhard Schölkopf, Matthias W. Seeger, Shai Shalev-Shwartz, John Shawe-Taylor, Yoram Singer, Alexander J. Smola, Sandor Szedmak, Ben Taskar, Ioannis Tsochantaridis, S.V.N Vishwanathan, Jason Weston.

About the Author:

S. V. N. Vishwanathan is an Assistant Professor of Statistics and Computer Science at Purdue University and Senior Researcher in the Statistical Machine Learning Program, National ICT Australia with an adjunct appointment at the Research School for Information Sciences and Engineering, Australian National University.