SIGNAL PROCESSING LETTERS 1 On-Line Learning for Active Pattern

@inproceedings{Park1996SIGNALPL,
  title={SIGNAL PROCESSING LETTERS 1 On-Line Learning for Active Pattern},
  author={R Park},
  year={1996}
}
| An adaptive on-line learning method is presented to faciliate pattern classiication using active sampling to identify optimal decision boundary for a stochas-tic oracle with minimum number of training samples. The strategy of sampling at the current estimate of the decision boundary is shown to be optimal compared to random sampling in the sense that the probability of convergence toward the true decision boundary at each step is maximized, ooering theoretical justiication on the popular… CONTINUE READING

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