Message from Dean - May 8th 2007
I am currently testing out a new version of the APF Bridge Component - If you notice any errors within this demo store please drop me a line.
from: The MIT Press
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Binding: Hardcover
Dewey Decimal Number: 006.31
EAN: 9780262026178
ISBN: 0262026171
Label: The MIT Press
Manufacturer: The MIT Press
Number Of Items: 1
Number Of Pages: 360
Publication Date: September 30, 2007
Publisher: The MIT Press
Studio: The MIT Press
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Product Description:
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 Bakır, 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, and Jason Weston
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