Articoli correlati a Predicting Structured Data
Sinossi
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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
L'autore
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.
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- EditoreMit Pr
- Data di pubblicazione2007
- ISBN 10 0262026171
- ISBN 13 9780262026178
- RilegaturaCopertina rigida
- LinguaInglese
- Numero di pagine348
- RedattoreBakir Gokhan, Hofmann Thomas, Schölkopf Bernhard, Smola Alexander J., Taskar Ben, Vishwanathan S. V. N.
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Predicting Structured Data
Da: Better World Books, Mishawaka, IN, U.S.A.
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Predicting Structured Data (Advances in Neural Information Processing Systems)
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Condizione: New. *Price HAS BEEN REDUCED by 10% until Monday, May 12 (weekend sale item)* 348 pp., hardcover, new in a fine dust jacket. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country. Codice articolo ZB1316032
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Predicting Structured Data (Neural Information Processing series)
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The MIT Press, Cambridge, MA, 2007
ISBN 10: 0262026171
ISBN 13: 9780262026178
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Hardcover. Condizione: Fine. Condizione sovraccoperta: Near Fine. 1st Edition. 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. Codice articolo 003177
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Predicting Structured Data (Neural Information Processing series)
Da: dsmbooks, Liverpool, Regno Unito
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Hardcover. Condizione: Very Good. Very Good. book. Codice articolo D7S9-1-M-0262026171-3
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