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Computers Intelligence (ai) & Semantics

Advanced Structured Prediction

edited by Sebastian Nowozin, Peter V. Gehler, Jeremy Jancsary & Christoph H. Lampert

Publisher
MIT Press
Initial publish date
Dec 2014
Category
Intelligence (AI) & Semantics, Computer Vision & Pattern Recognition
  • Hardback

    ISBN
    9780262028370
    Publish Date
    Dec 2014
    List Price
    $86.00

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Description

An overview of recent work in the field of structured prediction, the building of predictive machine learning models for interrelated and dependent outputs.

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.

Contributors
Jonas Behr, Yutian Chen, Fernando De La Torre, Justin Domke, Peter V. Gehler, Andrew E. Gelfand, Sébastien Giguère, Amir Globerson, Fred A. Hamprecht, Minh Hoai, Tommi Jaakkola, Jeremy Jancsary, Joseph Keshet, Marius Kloft, Vladimir Kolmogorov, Christoph H. Lampert, François Laviolette, Xinghua Lou, Mario Marchand, André F. T. Martins, Ofer Meshi, Sebastian Nowozin, George Papandreou, Daniel Prua, Gunnar Rätsch, Amélie Rolland, Bogdan Savchynskyy, Stefan Schmidt, Thomas Schoenemann, Gabriele Schweikert, Ben Taskar, Sinisa Todorovic, Max Welling, David Weiss, Thomá Werner, Alan Yuille, Stanislav Živný

About the authors

Sebastian Nowozin is a Researcher in the Machine Learning and Perception group (MLP) at Microsoft Research, Cambridge, England.

Sebastian Nowozin's profile page

Peter V. Gehler is a Senior Researcher in the Perceiving Systems group at the Max Planck Institute for Intelligent Systems, Tü bingen, Germany.

Peter V. Gehler's profile page

Jeremy Jancsary is a Senior Research Scientist at Nuance Communications, Vienna.

Jeremy Jancsary's profile page

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.

Christoph H. Lampert's profile page

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