State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.
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
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Gökhan Bakir is Research Scientist at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany.
Thomas Hofmann is a Director of Engineering at Google's Engineering Center in Zurich and Adjunct Associate Professor of Computer Science at Brown University.
Bernhard Schölkopf is Director at the Max Planck Institute for Intelligent Systems in Tübingen, Germany. He is coauthor of Learning with Kernels (2002) and is a coeditor of Advances in Kernel Methods: Support Vector Learning (1998), Advances in Large-Margin Classifiers (2000), and Kernel Methods in Computational Biology (2004), all published by the MIT Press.
Alexander J. Smola is Senior Principal Researcher and Machine Learning Program Leader at National ICT Australia/Australian National University, Canberra.
Ben Taskar is Assistant Professor in the Computer and Information Science Department at the University of Pennsylvania.
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.
Jason Weston is a Research Scientist at NEC Labs America.
Gökhan Bakir is Research Scientist at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany.
Bernhard Schölkopf is Director at the Max Planck Institute for Intelligent Systems in Tübingen, Germany. He is coauthor of Learning with Kernels (2002) and is a coeditor of Advances in Kernel Methods: Support Vector Learning (1998), Advances in Large-Margin Classifiers (2000), and Kernel Methods in Computational Biology (2004), all published by the MIT Press.
Thomas Hofmann is a Director of Engineering at Google's Engineering Center in Zurich and Adjunct Associate Professor of Computer Science at Brown University.
Mehryar Mohri is Professor of Computer Science at New York University's Courant Institute of Mathematical Sciences and a Research Consultant at Google Research.
Jason Weston is a Research Scientist at NEC Labs America.
Daniel Marcu is Director of Strategic Initiatives at the Information Sciences Institute and Research Associate Professor in the Department of Computer Science at the University of Southern California.
Yann LeCun is Head of the Image Processing Research Department at AT&T Labs-Research.
David A McAllester is an Assistant Professor of Computer Science at MIT.
Zoubin Ghahramani is Lecturer in the Gatsby Computational Neuroscience Unit at University College London.
Alexander J. Smola is Senior Principal Researcher and Machine Learning Program Leader at National ICT Australia/Australian National University, Canberra.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
EUR 12,81 expédition depuis Etats-Unis vers France
Destinations, frais et délaisVendeur : Better World Books, Mishawaka, IN, Etats-Unis
Etat : Very Good. Used book that is in excellent condition. May show signs of wear or have minor defects. N° de réf. du vendeur 18050534-6
Quantité disponible : 1 disponible(s)
Vendeur : MODLITBOOKS, San Francisco, CA, Etats-Unis
Hardcover. Etat : Fine. Etat de la jaquette : 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. N° de réf. du vendeur 003177
Quantité disponible : 1 disponible(s)
Vendeur : dsmbooks, Liverpool, Royaume-Uni
Hardcover. Etat : Very Good. Very Good. SHIPS FROM MULTIPLE LOCATIONS. book. N° de réf. du vendeur D7S9-1-M-0262026171-3
Quantité disponible : 1 disponible(s)