Difference between revisions of "Martins et al 2010"
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=== Summary === | === Summary === | ||
| − | + | This paper generalizes the loss function of CRFs, structured SVMs, structured perceptron, and Softmax-margin CRFs into a single loss function, and then derives an online learning algorithm that can be used to learn with that more general loss function. For the hinge loss, the learning algorithm reduces to MIRA. | |
=== Method === | === Method === | ||
| Line 12: | Line 12: | ||
=== Related Papers === | === Related Papers === | ||
| + | MIRA | ||
| + | CRF | ||
| + | Softmax-margin CRFs | ||
In progress by [[User:Jmflanig]] | In progress by [[User:Jmflanig]] | ||
Revision as of 10:13, 1 October 2011
Citation and Online Link
A. F. T. Martins, K. Gimpel. N. A. Smith, E. P. Xing, P. M. Q. Aguiar, M. A. T. Figueiredo, 2010. Aggressive Online Learning of Structured Classifiers. Technical report CMU-ML-10-109.
Summary
This paper generalizes the loss function of CRFs, structured SVMs, structured perceptron, and Softmax-margin CRFs into a single loss function, and then derives an online learning algorithm that can be used to learn with that more general loss function. For the hinge loss, the learning algorithm reduces to MIRA.
Method
Experimental Result
Related Papers
MIRA CRF Softmax-margin CRFs
In progress by User:Jmflanig
