Advanced Structured Prediction

Advanced Structured Prediction

4.11 - 1251 ratings - Source

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, TA¼bingen, 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, SAcbastien GiguAure, Amir Globerson, Fred A. Hamprecht, Minh Hoai, Tommi Jaakkola, Jeremy Jancsary, Joseph Keshet, Marius Kloft, Vladimir Kolmogorov, Christoph H. Lampert, FranAsois Laviolette, Xinghua Lou, Mario Marchand, AndrAc F. T. Martins, Ofer Meshi, Sebastian Nowozin, George Papandreou, Daniel PruAia, Gunnar RActsch, AmAclie Rolland, Bogdan Savchynskyy, Stefan Schmidt, Thomas Schoenemann, Gabriele Schweikert, Ben Taskar, Sinisa Todorovic, Max Welling, David Weiss, ThomAiAi Werner, Alan Yuille, Stanislav A½ivnA½In Intl. Conf. on Principles and Practice of Constraint Programming (CP), pages 210a€“224. Springer, 2011. V. Dalmau, P. G. ... Computers and Intractability: A Guide to the Theory of NP-Completeness. W.H. Freeman, 1979. ... In Allerton Conf. on Communication, Control and Computing, pages 64a€“73. Curran Associates, Inc.

Title:Advanced Structured Prediction
Author: Sebastian Nowozin, Peter V. Gehler, Jeremy Jancsary, Christoph H. Lampert
Publisher:MIT Press - 2014-11-21

You must register with us as either a Registered User before you can Download this Book. You'll be greeted by a simple sign-up page.

Once you have finished the sign-up process, you will be redirected to your download Book page.

How it works:
  • 1. Register a free 1 month Trial Account.
  • 2. Download as many books as you like (Personal use)
  • 3. Cancel the membership at any time if not satisfied.

Click button below to register and download Ebook
Privacy Policy | Contact | DMCA