Predicting structured data /
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| Other Authors: | |
| Format: | Book |
| Language: | English |
| Published: |
Cambridge, Mass. :
MIT Press,
©2007.
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| Series: | Advances in neural information processing systems
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| Subjects: | |
| Online Access: | http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=202394 |
Table of Contents:
- Measuring Similarity with Kernels
- Discriminative Models
- Modeling Structure via Graphical Models
- Joint Kernel Maps / Jason Weston [and others]
- Support Vector Machine Learning for Interdependent and Structured Output Spaces / Yasemin Altun, Thomas Hofmann, and Ioannis Tsochandiridis
- Efficient Algorithms for Max-Margin Structured Classification / Juho Rousu [and others]
- Discriminative Learning of Prediction Suffix Trees with the Perceptron Algorithm / Ofer Dekel, Shai Shalev-Shwartz, and Yoram Singer
- A General Regression Framework for Learning String-to-String Mappings / Corinna Cortes, Mehryar Mohri, and Jason Weston
- Learning as Search Optimization / Hal Daume III and Daniel Marcu
- Energy-Based Models / Yann LeCun [and others]
- Generalization Bounds and Consistency for Structured Labeling / David McAllester
- Kernel Conditional Graphical Models / Fernando Perez-Cruz, Zoubin Ghahramani, and Massimiliano Pontil
- Density Estimation of Structured Outputs in Reproducing Kernel Hilbert Spaces / Yasemin Altun and Alex J. Smola
- Gaussian Process Belief Propagation / Matthias W. Seeger.