An adaptive learning approach for noisy data streams

Abstract

Two critical challenges typically associated with mining data streams are concept drift and data contamination. To address these challenges, we seek learning techniques and models that are robust to noise and can adapt to changes in timely fashion. We approach the stream-mining problem using a statistical estimation framework, and propose a fast and robust… (More)
DOI: 10.1109/ICDM.2004.10049

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Cite this paper

@article{Chu2004AnAL, title={An adaptive learning approach for noisy data streams}, author={Fang Chu and Yizhou Wang and Carlo Zaniolo}, journal={Fourth IEEE International Conference on Data Mining (ICDM'04)}, year={2004}, pages={351-354} }