Predicting Structured Data

Erscheinungsjahr 2007
ISBN: 978-0-262-52804-7
Verlag: MIT Press

Buch, Englisch, 362 Seiten, Paperback, Format (B × H): 203 mm x 254 mm, Gewicht: 776 g

Reihe: Neural Information Processing series

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

Autoren/Hrsg.

Bakir, Gokhan

BakIr, Gökhan

Hofmann, Thomas

Scholkopf, Bernhard

Schölkopf, Bernhard

Smola, Alexander J.

Taskar, Ben

Vishwanathan, S.V.N

Weitere Mitwirkende

Weston, Jason

BakIr, Gökhan

Bousquet, Olivier

Mann, Tobias

Noble, William Stafford

Schölkopf, Bernhard

Altun, Yasemin

Hofmann, Thomas

Tsochandiridis, Ioannis

Rousu, Juho

Saunders, Craig

Szedmak, Sander

Shawe-Taylor, John

Dekel, Ofer

Shalev-Shwartz, Shai

Singer, Yoram

Cortes, Corinna

Mohri, Mehryar

III, Hal Daumé

Marcu, Daniel

LeCun, Yann

Chopra, Sumit

Hadsell, Raia

Ranzato, Marc'Aurelio

Huang, Fu Jie

McAllester, David A.

Pérez-Cruz, Fernando

Ghahramani, Zoubin

Pontil, Massimiliano

Smola, Alexander J.

Seeger, Matthias

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen

Über Autor(innen)

Hofmann, Thomas
Thomas Hofmann is a Director of Engineering at Google's Engineering Center in Zurich and Adjunct Associate Professor of Computer Science at Brown University.

BakIr, Gökhan
Gökhan Bakir is Research Scientist at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany.

Schölkopf, Bernhard
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.

Vishwanathan, S.V.N
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.

McAllester, David A.
David A McAllester is an Assistant Professor of Computer Science at MIT.

Hofmann, Thomas
Thomas Hofmann is a Director of Engineering at Google's Engineering Center in Zurich and Adjunct Associate Professor of Computer Science at Brown University.

LeCun, Yann
Yann LeCun is Head of the Image Processing Research Department at AT&T Labs-Research.

Taskar, Ben
Ben Taskar is Assistant Professor in the Computer and Information Science Department at the University of Pennsylvania.

Weston, Jason
Jason Weston is a Research Scientist at NEC Labs America.

Smola, Alexander J.
Alexander J. Smola is Senior Principal Researcher and Machine Learning Program Leader at National ICT Australia/Australian National University, Canberra.

Mohri, Mehryar
Mehryar Mohri is Professor of Computer Science at New York University's Courant Institute of Mathematical Sciences and a Research Consultant at Google Research.

BakIr, Gökhan
Gökhan Bakir is Research Scientist at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany.

Schölkopf, Bernhard
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.

Marcu, Daniel
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.

Ghahramani, Zoubin
Zoubin Ghahramani is Lecturer in the Gatsby Computational Neuroscience Unit at University College London.

Smola, Alexander J.
Alexander J. Smola is Senior Principal Researcher and Machine Learning Program Leader at National ICT Australia/Australian National University, Canberra.

Gökhan Bakir is Research Scientist at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany.