105 citations · 161 across the 15 of their papers we have counts for
6 papers · 1 filter
FAIRification of MLC data
Ana Kostovska, Jasmin Bogatinovski, Andrej Treven +3
The multi-label classification (MLC) task has increasingly been receiving interest from the machine learning (ML) community, as evidenced by the growing number of papers and method…
Explainable Model-specific Algorithm Selection for Multi-Label Classification
Ana Kostovska, Carola Doerr, Sašo Džeroski +3
Multi-label classification (MLC) is an ML task of predictive modeling in which a data instance can simultaneously belong to multiple classes. MLC is increasingly gaining interest i…
Discover the Mysteries of the Maya: Selected Contributions from the Machine Learning Challenge & The Discovery Challenge Workshop at ECML PKDD 2021
Dragi Kocev, Nikola Simidjievski, Ana Kostovska +2
The volume contains selected contributions from the Machine Learning Challenge "Discover the Mysteries of the Maya", presented at the Discovery Challenge Track of The European Conf…
Semi-supervised Predictive Clustering Trees for (Hierarchical) Multi-label Classification
Jurica Levatić, Michelangelo Ceci, Dragi Kocev +1
Semi-supervised learning (SSL) is a common approach to learning predictive models using not only labeled examples, but also unlabeled examples. While SSL for the simple tasks of cl…
Current Trends in Deep Learning for Earth Observation: An Open-source Benchmark Arena for Image Classification
Ivica Dimitrovski, Ivan Kitanovski, Dragi Kocev +1
We present AiTLAS: Benchmark Arena -- an open-source benchmark suite for evaluating state-of-the-art deep learning approaches for image classification in Earth Observation (EO). To…
AiTLAS: Artificial Intelligence Toolbox for Earth Observation
Ivica Dimitrovski, Ivan Kitanovski, Panče Panov +2
The AiTLAS toolbox (Artificial Intelligence Toolbox for Earth Observation) includes state-of-the-art machine learning methods for exploratory and predictive analysis of satellite i…