9 citations · 13 across the 4 of their papers we have counts for
5 papers
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…
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…
Combined Cleaning and Resampling Algorithm for Multi-Class Imbalanced Data with Label Noise
Michał Koziarski, Michał Woźniak, Bartosz Krawczyk
The imbalanced data classification is one of the most crucial tasks facing modern data analysis. Especially when combined with other difficulty factors, such as the presence of noi…
Uniqueness of Medical Data Mining: How the new technologies and data they generate are transforming medicine
Krzysztof J. Cios, Bartosz Krawczyk, Jacquelyne Cios +1
The paper describes how the new technologies and data they generate are transforming medicine. It stresses the uniqueness of heterogeneous medical data and the ways of dealing with…
Monotonic classification: an overview on algorithms, performance measures and data sets
José-Ramón Cano, Pedro Antonio Gutiérrez, Bartosz Krawczyk +2
Currently, knowledge discovery in databases is an essential step to identify valid, novel and useful patterns for decision making. There are many real-world scenarios, such as bank…