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書誌詳細
| 刊年 | 2014 |
| G/SMD | リモートファイル |
| 形態 | 1 online resource (ix, 415 p.) : ill. |
| シリーズ名 | Neural information processing series
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| 注記 | Includes bibliographical references and index
Restricted to subscribers or individual electronic text purchasers
The goal of structured prediction is to build machine learning models that predict relational information that itself has structure, such as being composed of multiple interrelated parts. These models, which reflect prior knowledge, task-specific relations, and constraints, are used in fields including computer vision, speech recognition, natural language processing, and computational biology. They can carry out such tasks as predicting a natural language sentence, or segmenting an image into meaningful components. These models are expressive and powerful, but exact computation is often intractable. A broad research effort in recent years has aimed at designing structured prediction models and approximate inference and learning procedures that are computationally efficient. This volume offers an overview of this recent research in order to make the work accessible to a broader research community. The chapters, by leading researchers in the field, cover a range of topics, including research trends, the linear programming relaxation approach, innovations in probabilistic modeling, recent theoretical progress, and resource-aware learning.Sebastian Nowozin is a Researcher in the Machine Learning and Perception group (MLP) at Microsoft Research, Cambridge, England. Peter V. Gehler is a Senior Researcher in the Perceiving Systems group at the Max Planck Institute for Intelligent Systems, TŠubingen, Germany. Jeremy Jancsary is a Senior Research Scientist at Nuance Communications, Vienna. Christoph H. Lampert is Assistant Professor at the Institute of Science and Technology Austria, where he heads a group for Computer Vision and Machine Learning. Contributors Jonas Behr, Yutian Chen, Fernando De La Torre, Justin Domke, Peter V. Gehler, Andrew E. Gelfand, Sébastien Gigur̀e, Amir Globerson, Fred A. Hamprecht, Minh Hoai, Tommi Jaakkola, Jeremy Jancsary, Joseph Keshet, Marius Kloft, Vladimir Kolmogorov, Christoph H. Lampert, Frano̧is Laviolette, Xinghua Lou, Mario Marchand, André F. T. Martins, Ofer Meshi, Sebastian Nowozin, George Papandreou, Daniel Pru - Ła, Gunnar R©Þtsch, Amélie Rolland, Bogdan Savchynskyy, Stefan Schmidt, Thomas Schoenemann, Gabriele Schweikert, Ben Taskar, Sinisa Todorovic, Max Welling, David Weiss, Thom ̀- Ł Werner, Alan Yuille, Stanislav - ưivn©ư
Also available in print
Mode of access: World Wide Web
Description based on PDF viewed 12/23/2015
URL:https://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=7008160(Abstract with links to resource) |
| 出版国 | アメリカ合衆国 |
| 標題言語 | 英語 |
| 本文言語 | 英語 |
| 著者情報 | Nowozin, Sebastian
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| ISBN | 9780262322959(: electronic bk)
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| 無効/取消ISBN | 9780262028370(: electronic bk)
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| 件名 | LCSH:Machinelearning
LCSH:Computeralgorithms
LCSH:Datastructures(Computerscience)
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| NCID | 7008160 |
| IDENT | https://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=7008160 |
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