A Bayesian Framework for Online Classifier Ensemble

@inproceedings{Bai2014ABF,
  title={A Bayesian Framework for Online Classifier Ensemble},
  author={Qinxun Bai and Henry Lam and Stan Sclaroff},
  booktitle={ICML},
  year={2014}
}
We propose a Bayesian framework for recursively estimating the classifier weights in online learning of a classifier ensemble. In contrast with past methods, such as stochastic gradient descent or online boosting, our framework estimates the weights in terms of evolving posterior distributions. For a specified class of loss functions, we show that it is possible to formulate a suitably defined likelihood function and hence use the posterior distribution as an approximation to the global… CONTINUE READING

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