50 citations · 199 across the 14 of their papers we have counts for
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Link Analysis meets Ontologies: Are Embeddings the Answer?
Sebastian Mežnar, Matej Bevec, Nada Lavrač +1
The increasing amounts of semantic resources offer valuable storage of human knowledge; however, the probability of wrong entries increases with the increased size. The development…
Prioritization of COVID-19-related literature via unsupervised keyphrase extraction and document representation learning
Blaž Škrlj, Marko Jukič, Nika Eržen +2
The COVID-19 pandemic triggered a wave of novel scientific literature that is impossible to inspect and study in a reasonable time frame manually. Current machine learning methods…
Semantic Reasoning from Model-Agnostic Explanations
Timen Stepišnik Perdih, Nada Lavrač, Blaž Škrlj
With the wide adoption of black-box models, instance-based \emph{post hoc} explanation tools, such as LIME and SHAP became increasingly popular. These tools produce explanations, p…
ReliefE: Feature Ranking in High-dimensional Spaces via Manifold Embeddings
Blaž Škrlj, Sašo Džeroski, Nada Lavrač +1
Feature ranking has been widely adopted in machine learning applications such as high-throughput biology and social sciences. The approaches of the popular Relief family of algorit…