Predicting Structured Data

Overview

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 ...

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Overview

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 [no dot over i], Olivier Bousquet,Sumit Chopra, Corinna Cortes, Hal Daumé III, Ofer Dekel, Zoubin Ghahramani, Raia Hadsell, ThomasHofmann, 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.NVishwanathan, Jason Weston Gökhan Bakir [no dot over i] is Research Scientist at the Max PlanckInstitute for Biological Cybernetics in Tübingen, Germany. Thomas Hofmann is a Director ofEngineering at Google's Engineering Center in Zurich and Adjunct Associate Professor of ComputerScience at Brown University. Bernhard Schölkopf is Director of the Max Planck Institute forBiological Cybernetics and Professor at the Technical University Berlin. Alexander J. Smola isSenior Principal Researcher and Machine Learning Program Leader at National ICT Australia/AustralianNational University, Canberra. Ben Taskar is Assistant Professor in the Computer and InformationScience Department at the University of Pennsylvania. S. V. N. Vishwanathan is Senior Researcher in the Statistical Machine Learning Program, National ICT Australia with an adjunct appointment at theResearch School for Information Sciences and Engineering, Australian National University.

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Meet the Author

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

Bernhard Schölkopf is Professor and Director at the Max Planck Institute for BiologicalCybernetics 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 inComputational Biology (2004), all published by the MIT Press.

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

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

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