18 citations · 20 across the 4 of their papers we have counts for
5 papers
Not All Unlabeled Data Are Equal: Unlabeled Data Selection for Semi-Supervised QSAR Modeling with Large Chemical Repositories
Oliver Majer, Saso Dzeroski, Jurica Levatic
Semi-supervised learning (SSL) is particularly attractive in domains where labels are expensive to obtain, while unlabeled examples are readily available. Quantitative Structure-Ac…
MAPLE: Multi-Path Adaptive Propagation with Level-Aware Embeddings for Hierarchical Multi-Label Image Classification
Boshko Koloski, Marjan Stoimchev, Jurica Levatić +2
Hierarchical multi-label classification (HMLC) is essential for modeling structured label dependencies in remote sensing. Yet existing approaches struggle in multi-path settings, w…
HELM: Hierarchical and Explicit Label Modeling with Graph Learning for Multi-Label Image Classification
Marjan Stoimchev, Boshko Koloski, Jurica Levatić +2
Hierarchical multi-label classification (HMLC) is essential for modeling complex label dependencies in remote sensing. Existing methods, however, struggle with multi-path hierarchi…
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…
Machine learning for predicting thermal power consumption of the Mars Express Spacecraft
Matej Petković, Redouane Boumghar, Martin Breskvar +7
The thermal subsystem of the Mars Express (MEX) spacecraft keeps the on-board equipment within its pre-defined operating temperatures range. To plan and optimize the scientific ope…