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Tracking changes using Kullback-Leibler divergence for the continual learning

Tracking changes using Kullback-Leibler divergence for the continual learning

Sebastian Basterrech
Michal Wo'zniak
ArXiv (abs)PDFHTML

Papers citing "Tracking changes using Kullback-Leibler divergence for the continual learning"

3 / 3 papers shown
Title
Tackling Virtual and Real Concept Drifts: An Adaptive Gaussian Mixture Model
Tackling Virtual and Real Concept Drifts: An Adaptive Gaussian Mixture Model
Gustavo H. F. M. Oliveira
Leandro L. Minku
Adriano Oliveira
61
35
0
11 Feb 2021
stream-learn -- open-source Python library for difficult data stream batch analysis
stream-learn -- open-source Python library for difficult data stream batch analysis
Pawel Ksieniewicz
P. Zyblewski
AI4TS
27
28
0
29 Jan 2020
Exponentially Weighted Moving Average Charts for Detecting Concept Drift
Exponentially Weighted Moving Average Charts for Detecting Concept Drift
Gordon J. Ross
N. Adams
D. Tasoulis
D. Hand
85
370
0
25 Dec 2012

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