67 citations · 283 across the 39 of their papers we have counts for
12 papers · 1 filter
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…
Sparse Orthogonal Regression Technique: A Spectral Framework for Equation Discovery, Approximation, and Integration
Sabin Roman, Ljupco Todorovski, Saso Dzeroski
We develop the Sparse Orthogonal Regression Technique (SORT), a sparse spectral framework for learning orthonormal-basis expansions from noisy and irregularly sampled data. SORT es…
Design Choices That Matter: A Functional ANOVA Analysis for Remote Sensing Multi-Label Classification
Maryam Gholami Shiri, Eva Tuba, Sašo Džeroski +2
Benchmarking deep learning (DL) models for multi-label classification (MLC) of remote sensing images (RSI) typically yields rankings that do not generalize beyond the evaluated dat…
Neuro-Evolved Heuristics for Variable Gapped Common Subsequence Identification
Marko Djukanović, Christian Blum, Aleksandar Kartelj +2
This study addresses the Variable Gapped Longest Common Subsequence Problem (VGLCSP), a variant of the classical longest common subsequence problem with additional gap constraints…
Limits of spectral learning under noise
Sabin Roman, Ljupco Todorovski, Saso Dzeroski +2
Learning functional relationships from noisy data is a central problem in scientific inference. Spectral methods approximate unknown functions by expanding them in a basis and esti…
Graph Instance Landscapes: When Structural Similarity Does (Not) Reflect Shortest-Path Performance
Maryam Gholami Shiri, Ivana Krminac, Marko Djukanović +3
Benchmarking shortest-path algorithms is commonly based on aggregate performance over heterogeneous graph sets, which limits insight into how different search paradigms react to in…
On Solving the Multiple Variable Gapped Longest Common Subsequence Problem
Marko Djukanović, Nikola Balaban, Christian Blum +3
This paper addresses the Variable Gapped Longest Common Subsequence (VGLCS) problem, a generalization of the classical LCS problem involving flexible gap constraints between consec…
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…
Benchmarking Machine Learning Approaches for Polarization Mapping in Ferroelectrics Using 4D-STEM
Matej Martinc, Goran Dražič, Anton Kokalj +5
Four-dimensional scanning transmission electron microscopy (4D-STEM) provides rich, atomic-scale insights into materials structures. However, extracting specific physical propertie…
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…
Uncertainty-Aware Extrapolation in Bayesian Oblique Trees
Viktor Andonovikj, Sašo Džeroski, Pavle Boškoski
Decision trees are widely used due to their interpretability and efficiency, but they struggle in regression tasks that require reliable extrapolation and well-calibrated uncertain…
Quantifying the Impact of Modules and Their Interactions in the PSO-X Framework
Christian L. Camacho-Villalón, Ana Nikolikj, Katharina Dost +3
The PSO-X framework incorporates dozens of modules that have been proposed for solving single-objective continuous optimization problems using particle swarm optimization. While mo…