Fast Concept Drift Detection Exploiting Product Quantization
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-68312-1_20
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4. Faber, K., Corizzo, R., Sniezynski, B., Baron, M., Japkowicz, N.: Watch: Wasserstein change point detection for high-dimensional time series data. In: 2021 IEEE International Conference on Big Data (Big Data), pp. 4450–4459. IEEE (2021)
5. Gözüaçık, O., Büyükçakır, A., Bonab, H., Can, F.: Unsupervised concept drift detection with a discriminative classifier. In: Proceedings of the 28th ACM CIKM, pp. 2365–2368 (2019)
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