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PRL
2007
118views more  PRL 2007»
13 years 12 months ago
Unifying multi-class AdaBoost algorithms with binary base learners under the margin framework
Multi-class AdaBoost algorithms AdaBooost.MO, -ECC and -OC have received a great attention in the literature, but their relationships have not been fully examined to date. In this...
Yijun Sun, Sinisa Todorovic, Jian Li
CSDA
2006
66views more  CSDA 2006»
14 years 14 days ago
A dynamic model of expected bond returns: A functional gradient descent approach
We propose a multivariate methodology based on Functional Gradient Descent to estimate and forecast time-varying expected bond returns. Backtesting our procedure on US monthly dat...
Francesco Audrino, Giovanni Barone-Adesi
ICML
2005
IEEE
15 years 1 months ago
Unifying the error-correcting and output-code AdaBoost within the margin framework
In this paper, we present a new interpretation of AdaBoost.ECC and AdaBoost.OC. We show that AdaBoost.ECC performs stage-wise functional gradient descent on a cost function, defin...
Yijun Sun, Sinisa Todorovic, Jian Li, Dapeng Wu
ICPR
2008
IEEE
15 years 1 months ago
Collaborative learning by boosting in distributed environments
In this paper we propose a new distributed learning method called distributed network boosting (DNB) algorithm for distributed applications. The learned hypotheses are exchanged b...
Shijun Wang, Changshui Zhang