4 citations · 10 across the 7 of their papers we have counts for
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cs.LG2020★ 4 cited
Adaptive Deep Forest for Online Learning from Drifting Data Streams
Łukasz Korycki, Bartosz Krawczyk
Learning from data streams is among the most vital fields of contemporary data mining. The online analysis of information coming from those potentially unbounded data sources allow…
cs.LG2020★ 3 cited
Adversarial Concept Drift Detection under Poisoning Attacks for Robust Data Stream Mining
Łukasz Korycki, Bartosz Krawczyk
Continuous learning from streaming data is among the most challenging topics in the contemporary machine learning. In this domain, learning algorithms must not only be able to hand…
cs.LG2020
Instance exploitation for learning temporary concepts from sparsely labeled drifting data streams
Łukasz Korycki, Bartosz Krawczyk
Continual learning from streaming data sources becomes more and more popular due to the increasing number of online tools and systems. Dealing with dynamic and everlasting problems…