Martins et al 2010

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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

The general loss function is:

Martins et al 2010 Loss Function.png

Different choices of and correspond to various well known loss functions. They are:

Martins et al 2010 Parameter Choices.png

The function minimized is the loss function with a regularizer:

Martins et al 2010 Learning Problem.png Martins et al Relarizer.png

Martins et al Regularize Coeff.png

The online learning algorithm proposed to minimize this function is called Dual Coordinate Ascent (DCA):

Martins et al 2010 DCA.png

The parameters can be updated using algorithm 2:

Martins et al 2010 Alg2.png

Experimental Result

Related Papers

MIRA CRF Softmax-margin CRFs

In progress by User:Jmflanig

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