no code implementations • 30 Jun 2023 • Ana Kostovska, Anja Jankovic, Diederick Vermetten, Sašo Džeroski, Tome Eftimov, Carola Doerr
Performance complementarity of solvers available to tackle black-box optimization problems gives rise to the important task of algorithm selection (AS).
no code implementations • 1 Jun 2023 • Ana Nikolikj, Sašo Džeroski, Mario Andrés Muñoz, Carola Doerr, Peter Korošec, Tome Eftimov
In black-box optimization, it is essential to understand why an algorithm instance works on a set of problem instances while failing on others and provide explanations of its behavior.
no code implementations • 15 May 2023 • Devis Tuia, Konrad Schindler, Begüm Demir, Gustau Camps-Valls, Xiao Xiang Zhu, Mrinalini Kochupillai, Sašo Džeroski, Jan N. van Rijn, Holger H. Hoos, Fabio Del Frate, Mihai Datcu, Jorge-Arnulfo Quiané-Ruiz, Volker Markl, Bertrand Le Saux, Rochelle Schneider
Earth observation (EO) is a prime instrument for monitoring land and ocean processes, studying the dynamics at work, and taking the pulse of our planet.
no code implementations • 3 May 2023 • Stefan Kramer, Mattia Cerrato, Sašo Džeroski, Ross King
The paper surveys automated scientific discovery, from equation discovery and symbolic regression to autonomous discovery systems and agents.
1 code implementation • 20 Feb 2023 • Sebastian Mežnar, Sašo Džeroski, Ljupčo Todorovski
We empirically show that HVAE can be trained efficiently with small corpora of mathematical expressions and can accurately encode expressions into a smooth low-dimensional latent space.
no code implementations • 24 Jan 2023 • Ana Kostovska, Diederick Vermetten, Sašo Džeroski, Panče Panov, Tome Eftimov, Carola Doerr
In this work, we evaluate a performance prediction model built on top of the extension of the recently proposed OPTION ontology.
no code implementations • 23 Nov 2022 • Ana Kostovska, Jasmin Bogatinovski, Andrej Treven, Sašo Džeroski, Dragi Kocev, Panče Panov
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 methods that appear in the literature.
no code implementations • 21 Nov 2022 • Ana Kostovska, Carola Doerr, Sašo Džeroski, Dragi Kocev, Panče Panov, Tome Eftimov
To address this algorithm selection problem, we investigate in this work the quality of an automated approach that uses characteristics of the datasets - so-called features - and a trained algorithm selector to choose which algorithm to apply for a given task.
no code implementations • 19 Jul 2022 • Jurica Levatić, Michelangelo Ceci, Dragi Kocev, Sašo Džeroski
Semi-supervised learning (SSL) is a common approach to learning predictive models using not only labeled examples, but also unlabeled examples.
1 code implementation • 15 Apr 2022 • Ana Kostovska, Diederick Vermetten, Sašo Džeroski, Carola Doerr, Peter Korošec, Tome Eftimov
In addition, we have shown that by using classifiers that take the features relevance on the model accuracy, we are able to predict the status of individual modules in the CMA-ES configurations.
no code implementations • 4 Mar 2022 • Jure Brence, Dragan Mihailović, Viktor Kabanov, Ljupčo Todorovski, Sašo Džeroski, Jaka Vodeb
Noisy intermediate-scale quantum (NISQ) devices are spearheading the second quantum revolution.
1 code implementation • 25 Nov 2021 • Urh Primožič, Blaž Škrlj, Sašo Džeroski, Matej Petković
The need for learning from unlabeled data is increasing in contemporary machine learning.
no code implementations • 3 Aug 2021 • Ana Kostovska, Matej Petković, Tomaž Stepišnik, Luke Lucas, Timothy Finn, José Martínez-Heras, Panče Panov, Sašo Džeroski, Alessandro Donati, Nikola Simidjievski, Dragi Kocev
We present GalaxAI - a versatile machine learning toolbox for efficient and interpretable end-to-end analysis of spacecraft telemetry data.
no code implementations • 28 Jun 2021 • Jasmin Bogatinovski, Ljupčo Todorovski, Sašo Džeroski, Dragi Kocev
Here, we analyze 40 MLC data sets by using 50 meta features describing different properties of the data.
no code implementations • 24 Apr 2021 • Ana Kostovska, Diederick Vermetten, Carola Doerr, Sašo Džeroski, Panče Panov, Tome Eftimov
Many platforms for benchmarking optimization algorithms offer users the possibility of sharing their experimental data with the purpose of promoting reproducible and reusable research.
no code implementations • 14 Feb 2021 • Jasmin Bogatinovski, Ljupčo Todorovski, Sašo Džeroski, Dragi Kocev
Several studies provide reviews of methods and datasets for MLC and a few provide empirical comparisons of MLC methods.
1 code implementation • 23 Jan 2021 • Blaž Škrlj, Sašo Džeroski, Nada Lavrač, Matej Petković
The utility of ReliefE for high-dimensional data sets is ensured by its implementation that utilizes sparse matrix algebraic operations.
Multi-Label Classification Vocal Bursts Intensity Prediction
1 code implementation • 1 Dec 2020 • Jure Brence, Ljupčo Todorovski, Sašo Džeroski
Equation discovery, also known as symbolic regression, is a type of automated modeling that discovers scientific laws, expressed in the form of equations, from observed data and expert knowledge.
1 code implementation • 23 Nov 2020 • Matej Petković, Dragi Kocev, Blaž Škrlj, Sašo Džeroski
In this work, we propose two novel (groups of) methods for unsupervised feature ranking and selection.
no code implementations • 10 Aug 2020 • Matej Petković, Sašo Džeroski, Dragi Kocev
This poses a variety of challenges for the existing machine learning methods: coping with dataset with a large number of examples that are described in a high-dimensional space and not all examples have labels provided.
no code implementations • 11 Feb 2020 • Blaž Škrlj, Sašo Džeroski, Nada Lavrač, Matej Petkovič
Black-box neural network models are widely used in industry and science, yet are hard to understand and interpret.
no code implementations • 1 Jul 2019 • Nikola Simidjievski, Ljupčo Todorovski, Juš Kocijan, Sašo Džeroski
In this paper, recent developments of the equation discovery method called process-based modeling, suited for nonlinear system identification, are elaborated and illustrated on two continuous-time case studies.
no code implementations • 21 Jun 2019 • Žiga Lukšič, Jovan Tanevski, Sašo Džeroski, Ljupčo Todorovski
This task involves numerous evaluations of a computationally expensive objective function.
1 code implementation • 3 Sep 2018 • Matej Petković, Redouane Boumghar, Martin Breskvar, Sašo Džeroski, Dragi Kocev, Jurica Levatić, Luke Lucas, Aljaž Osojnik, Bernard Ženko, Nikola Simidjievski
The thermal subsystem of the Mars Express (MEX) spacecraft keeps the on-board equipment within its pre-defined operating temperatures range.
no code implementations • 20 Feb 2017 • Matej Mihelčić, Goran Šimić, Mirjana Babić Leko, Nada Lavrač, Sašo Džeroski, Tomislav Šmuc
However, in some instances, as with the attributes: testosterone, the imaging attribute Spatial Pattern of Abnormalities for Recognition of Early AD, as well as the levels of leptin and angiopoietin-2 in plasma, we corroborated previously debatable findings or provided additional information about these variables and their association with AD pathogenesis.
no code implementations • 13 Jun 2016 • Matej Mihelčić, Sašo Džeroski, Nada Lavrač, Tomislav Šmuc
In contrast to previous approaches that typically create one smaller set of redescriptions satisfying a pre-defined set of constraints, we introduce a framework that creates large and heterogeneous redescription set from which user/expert can extract compact sets of differing properties, according to its own preferences.