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Climate Code Foundation
Poster presented at the VSMF Symposium held in the Unilever Centre on 2011-01-17Climate Code Foundation - who are we? A non-profit organisation founded in August 2010; our goal is to promote the public understanding of climate science, by increasing the visibility and clarity of the software used in climate science and by encouraging climate scientists to do the same, by encouraging good software development and management practices among climate scientists and by encouraging the publication of climate science software as Open Source. [http://www.climatecode.org/
Totally Corrective Multiclass Boosting with Binary Weak Learners
In this work, we propose a new optimization framework for multiclass boosting
learning. In the literature, AdaBoost.MO and AdaBoost.ECC are the two
successful multiclass boosting algorithms, which can use binary weak learners.
We explicitly derive these two algorithms' Lagrange dual problems based on
their regularized loss functions. We show that the Lagrange dual formulations
enable us to design totally-corrective multiclass algorithms by using the
primal-dual optimization technique. Experiments on benchmark data sets suggest
that our multiclass boosting can achieve a comparable generalization capability
with state-of-the-art, but the convergence speed is much faster than stage-wise
gradient descent boosting. In other words, the new totally corrective
algorithms can maximize the margin more aggressively.Comment: 11 page
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