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ORCIDSaso Dzeroski
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- affiliation: Jožef Stefan Institute, Department of Intelligent Systems
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2020 – today
- 2024
[j124]Viktor Andonovikj
, Pavle Boskoski, Saso Dzeroski, Biljana Mileva-Boshkoska:
Survival analysis as semi-supervised multi-target regression for time-to-employment prediction using oblique predictive clustering trees. Expert Syst. Appl. 235: 121246 (2024)- [j123]Gordana Ispirova, Tome Eftimov, Saso Dzeroski, Barbara Korousic-Seljak:
MsGEN: Measuring generalization of nutrient value prediction across different recipe datasets. Expert Syst. Appl. 237(Part B): 121507 (2024) - [j122]Jurica Levatic, Michelangelo Ceci, Dragi Kocev, Saso Dzeroski:
Semi-Supervised Predictive Clustering Trees for (Hierarchical) Multi-Label Classification. Int. J. Intell. Syst. 2024: 1-21 (2024) - [j121]Nina Omejc, Bostjan Gec, Jure Brence, Ljupco Todorovski, Saso Dzeroski:
Probabilistic grammars for modeling dynamical systems from coarse, noisy, and partial data. Mach. Learn. 113(10): 7689-7721 (2024) - [j120]Marjan Stoimchev, Jurica Levatic, Dragi Kocev, Saso Dzeroski:
Semi-Supervised Multi-Label Classification of Land Use/Land Cover in Remote Sensing Images With Predictive Clustering Trees and Ensembles. IEEE Trans. Geosci. Remote. Sens. 62: 1-16 (2024) - [i34]Sebastian Meznar, Saso Dzeroski, Ljupco Todorovski:
Quantifying Behavioural Distance Between Mathematical Expressions. CoRR abs/2408.11515 (2024) - 2023
- [j119]Jure Brence, Saso Dzeroski, Ljupco Todorovski:
Dimensionally-consistent equation discovery through probabilistic attribute grammars. Inf. Sci. 632: 742-756 (2023) - [j118]Jure Brence, Jovan Tanevski, Jennifer Adams, Edward Malina, Saso Dzeroski:
Surrogate models of radiative transfer codes for atmospheric trace gas retrievals from satellite observations. Mach. Learn. 112(4): 1337-1363 (2023) - [j117]Matej Petkovic, Saso Dzeroski, Dragi Kocev:
Feature ranking for semi-supervised learning. Mach. Learn. 112(11): 4379-4408 (2023) - [j116]Sebastian Meznar, Saso Dzeroski, Ljupco Todorovski:
Efficient generator of mathematical expressions for symbolic regression. Mach. Learn. 112(11): 4563-4596 (2023) - [j115]Sebastian Meznar, Saso Dzeroski, Ljupco Todorovski:
Correction to: efficient generator of mathematical expressions for symbolic regression. Mach. Learn. 112(12): 5191 (2023) - [j114]Jure Brence, Dragan Mihailovic, Viktor V. Kabanov, Ljupco Todorovski, Saso Dzeroski, Jaka Vodeb:
Boosting the performance of quantum annealers using machine learning. Quantum Mach. Intell. 5(1): 1-11 (2023) - [j113]Marjan Stoimchev, Dragi Kocev, Saso Dzeroski:
Deep Network Architectures as Feature Extractors for Multi-Label Classification of Remote Sensing Images. Remote. Sens. 15(2): 538 (2023) - [j112]Rok Novak, Johanna Amalia Robinson, Tjasa Kanduc, Dimosthenis Sarigiannis, Saso Dzeroski, David Kocman:
Empowering Participatory Research in Urban Health: Wearable Biometric and Environmental Sensors for Activity Recognition. Sensors 23(24): 9890 (2023) - [j111]Matej Petkovic, Jurica Levatic, Dragi Kocev, Martin Breskvar, Saso Dzeroski:
CLUSplus: A decision tree-based framework for predicting structured outputs. SoftwareX 24: 101526 (2023) - [j110]Ana Kostovska, Diederick Vermetten, Carola Doerr, Saso Dzeroski, Pance Panov, Tome Eftimov:
OPTION: OPTImization Algorithm Benchmarking ONtology. IEEE Trans. Evol. Comput. 27(6): 1618-1632 (2023) - [c171]Aljaz Osojnik, Pance Panov, Saso Dzeroski:
iSOUP-SymRF: Symbolic Feature Ranking with Random Forests in Online Multi-target Regression. DS 2023: 48-63 - [c170]Ana Kostovska, Diederick Vermetten, Saso Dzeroski, Pance Panov, Tome Eftimov, Carola Doerr:
Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms. EvoApplications@EvoStar 2023: 253-268 - [c169]Ana Kostovska, Anja Jankovic, Diederick Vermetten, Saso Dzeroski, Tome Eftimov, Carola Doerr:
Comparing Algorithm Selection Approaches on Black-Box Optimization Problems. GECCO Companion 2023: 495-498 - [c168]Ana Nikolikj, Saso Dzeroski, Mario Andrés Muñoz, Carola Doerr, Peter Korosec, Tome Eftimov:
Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem Instances. GECCO 2023: 529-537 - [c167]Martha Roseberry, Saso Dzeroski, Albert Bifet, Alberto Cano:
Aging and rejuvenating strategies for fading windows in multi-label classification on data streams. SAC 2023: 390-397 - [d3]Rok Novak, Johanna Amalia Robinson, Tjasa Kanduc, Dimosthenis Sarigiannis, Saso Dzeroski, David Kocman:
Minute-Level Human Activity and Particulate Matter Exposure Dataset from Ljubljana, Slovenia. Zenodo, 2023
- [d2]Nina Omejc, Bostjan Gec, Jure Brence, Ljupco Todorovski, Saso Dzeroski:
Dynobench - extended Strogatz benchmark for system identification methods. Zenodo, 2023 - [i33]Ana Kostovska, Diederick Vermetten, Saso Dzeroski, Pance Panov, Tome Eftimov, Carola Doerr:
Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms. CoRR abs/2301.09876 (2023) - [i32]Sebastian Meznar, Saso Dzeroski, Ljupco Todorovski:
Efficient Generator of Mathematical Expressions for Symbolic Regression. CoRR abs/2302.09893 (2023) - [i31]Stefan Kramer, Mattia Cerrato, Saso Dzeroski, Ross D. King:
Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems. CoRR abs/2305.02251 (2023) - [i30]Devis Tuia, Konrad Schindler, Begüm Demir, Gustau Camps-Valls, Xiao Xiang Zhu, Mrinalini Kochupillai, Saso Dzeroski, Jan N. van Rijn, Holger H. Hoos, Fabio Del Frate, Mihai Datcu, Jorge-Arnulfo Quiané-Ruiz, Volker Markl, Bertrand Le Saux, Rochelle Schneider:
Artificial intelligence to advance Earth observation: a perspective. CoRR abs/2305.08413 (2023) - [i29]Ana Nikolikj, Saso Dzeroski, Mario Andrés Muñoz, Carola Doerr, Peter Korosec, Tome Eftimov:
Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem Instances. CoRR abs/2306.00479 (2023) - [i28]Ana Kostovska, Anja Jankovic, Diederick Vermetten, Saso Dzeroski, Tome Eftimov, Carola Doerr:
Comparing Algorithm Selection Approaches on Black-Box Optimization Problems. CoRR abs/2306.17585 (2023) - [i27]Hector Zenil, Jesper Tegnér, Felipe S. Abrahão, Alexander Lavin, Vipin Kumar, Jeremy G. Frey, Adrian Weller, Larisa N. Soldatova, Alan R. Bundy, Nicholas R. Jennings, Koichi Takahashi, Lawrence Hunter, Saso Dzeroski, Andrew Briggs, Frederick D. Gregory, Carla P. Gomes, Christopher K. I. Williams, Jon Rowe, James A. Evans, Hiroaki Kitano, Joshua B. Tenenbaum, Ross D. King:
The Future of Fundamental Science Led by Generative Closed-Loop Artificial Intelligence. CoRR abs/2307.07522 (2023) - [i26]Saso Dzeroski, Holger H. Hoos, Bertrand Le Saux, Leendert van der Torre, Ana Kostovska:
Space and Artificial Intelligence (Dagstuhl Seminar 23461). Dagstuhl Reports 13(11): 72-102 (2023) - 2022
- [j109]Bijit Roy, Tomaz Stepisnik, The Pooled Resource Open-Access A. L. S. Clinical Trials Consortium, Celine Vens, Saso Dzeroski:
Survival analysis with semi-supervised predictive clustering trees. Comput. Biol. Medicine 141: 105001 (2022) - [j108]Jasmin Bogatinovski, Ljupco Todorovski, Saso Dzeroski, Dragi Kocev:
Comprehensive comparative study of multi-label classification methods. Expert Syst. Appl. 203: 117215 (2022) - [j107]Jasmin Bogatinovski, Ljupco Todorovski, Saso Dzeroski, Dragi Kocev:
Explaining the performance of multilabel classification methods with data set properties. Int. J. Intell. Syst. 37(9): 6080-6122 (2022) - [j106]Milka Ljoncheva, Tomaz Stepisnik, Tina Kosjek, Saso Dzeroski:
Machine learning for identification of silylated derivatives from mass spectra. J. Cheminformatics 14(1): 62 (2022) - [j105]Matej Petkovic, Michelangelo Ceci, Gianvito Pio, Blaz Skrlj, Kristian Kersting, Saso Dzeroski:
Relational tree ensembles and feature rankings. Knowl. Based Syst. 251: 109254 (2022) - [j104]Blaz Skrlj, Saso Dzeroski, Nada Lavrac, Matej Petkovic:
ReliefE: feature ranking in high-dimensional spaces via manifold embeddings. Mach. Learn. 111(1): 273-317 (2022) - [j103]Mihael Simonic, Matevz Majcen Hrovat, Saso Dzeroski, Ales Ude, Bojan Nemec:
Determining Exception Context in Assembly Operations from Multimodal Data. Sensors 22(20): 7962 (2022) - [c166]Bostjan Gec, Nina Omejc, Jure Brence, Saso Dzeroski, Ljupco Todorovski:
Discovery of Differential Equations Using Probabilistic Grammars. DS 2022: 22-31 - [c165]Ana Kostovska, Diederick Vermetten, Saso Dzeroski, Carola Doerr, Peter Korosec, Tome Eftimov:
The importance of landscape features for performance prediction of modular CMA-ES variants. GECCO 2022: 648-656 - [c164]Ana Kostovska, Carola Doerr, Saso Dzeroski, Dragi Kocev, Pance Panov, Tome Eftimov:
Explainable Model-specific Algorithm Selection for Multi-Label Classification. SSCI 2022: 39-46 - [d1]Ana Kostovska, Diederick Vermetten, Saso Dzeroski, Carola Doerr, Peter Korosec, Tome Eftimov:
Linking Problem Landscape Features with the Performance of Individual CMA-ES Modules - Data. Zenodo, 2022 - [i25]Jure Brence, Dragan Mihailovic, Viktor V. Kabanov, Ljupco Todorovski, Saso Dzeroski, Jaka Vodeb:
Boosting the Performance of Quantum Annealers using Machine Learning. CoRR abs/2203.02360 (2022) - [i24]Ana Kostovska, Diederick Vermetten, Saso Dzeroski, Carola Doerr, Peter Korosec, Tome Eftimov:
The Importance of Landscape Features for Performance Prediction of Modular CMA-ES Variants. CoRR abs/2204.07431 (2022) - [i23]Jurica Levatic, Michelangelo Ceci, Dragi Kocev, Saso Dzeroski:
Semi-supervised Predictive Clustering Trees for (Hierarchical) Multi-label Classification. CoRR abs/2207.09237 (2022) - [i22]Ana Kostovska, Carola Doerr, Saso Dzeroski, Dragi Kocev, Pance Panov, Tome Eftimov:
Explainable Model-specific Algorithm Selection for Multi-Label Classification. CoRR abs/2211.11227 (2022) - [i21]Ana Kostovska, Diederick Vermetten, Carola Doerr, Saso Dzeroski, Pance Panov, Tome Eftimov:
OPTION: OPTImization Algorithm Benchmarking ONtology. CoRR abs/2211.11332 (2022) - [i20]Ana Kostovska, Jasmin Bogatinovski, Andrej Treven, Saso Dzeroski, Dragi Kocev, Pance Panov:
FAIRification of MLC data. CoRR abs/2211.12757 (2022) - 2021
- [j102]Martin Breskvar, Saso Dzeroski:
Multi-Target Regression Rules With Random Output Selections. IEEE Access 9: 10509-10522 (2021) - [j101]Matej Petkovic, Ivica Slavkov, Dragi Kocev, Saso Dzeroski:
Biomarker discovery by feature ranking: Evaluation on a case study of embryonal tumors. Comput. Biol. Medicine 128: 104143 (2021) - [j100]Stevanche Nikoloski, Dragi Kocev, Jurica Levatic, David P. Wall, Saso Dzeroski:
Exploiting partially-labeled data in learning predictive clustering trees for multi-target regression: A case study of water quality assessment in Ireland. Ecol. Informatics 61: 101161 (2021) - [j99]Rok Piltaver, Mitja Lustrek, Saso Dzeroski, Martin Gjoreski, Matjaz Gams:
Learning comprehensible and accurate hybrid trees. Expert Syst. Appl. 164: 113980 (2021) - [j98]Matej Petkovic, Dragi Kocev, Blaz Skrlj, Saso Dzeroski:
Ensemble- and distance-based feature ranking for unsupervised learning. Int. J. Intell. Syst. 36(7): 3068-3086 (2021) - [j97]Jure Brence, Ljupco Todorovski, Saso Dzeroski:
Probabilistic grammars for equation discovery. Knowl. Based Syst. 224: 107077 (2021) - [c163]Urh Primozic, Blaz Skrlj, Saso Dzeroski, Matej Petkovic:
Unsupervised Feature Ranking via Attribute Networks. DS 2021: 334-343 - [c162]Ana Kostovska, Diederick Vermetten, Carola Doerr, Saso Dzeroski, Pance Panov, Tome Eftimov:
OPTION: optimization algorithm benchmarking ontology. GECCO Companion 2021: 239-240 - [c161]Stefan Popov, Janja Snoj Tratnik, Martin Breskvar, Darja Mazej, Milena Horvat, Saso Dzeroski:
Modeling the Association Between Prenatal Exposure to Mercury and Neurodevelopment of Children. ICT Innovations 2021: 85-97 - [c160]Stefan Popov, Katja Kavkler, Saso Dzeroski:
Using Machine Learning to Identify Factors Contributing to Mould in the Celje Ceiling Painting. MIPRO 2021: 217-222 - [c159]Stefan Popov, Janja Snoj Tratnik, Martin Breskvar, Darja Mazej, Milena Horvat, Saso Dzeroski:
Relating Prenatal Hg Exposure and Neurological Development in Children with Machine Learning. MIPRO 2021: 389-394 - [i19]Blaz Skrlj, Saso Dzeroski, Nada Lavrac, Matej Petkovic:
ReliefE: Feature Ranking in High-dimensional Spaces via Manifold Embeddings. CoRR abs/2101.09577 (2021) - [i18]Jasmin Bogatinovski, Ljupco Todorovski, Saso Dzeroski, Dragi Kocev:
Comprehensive Comparative Study of Multi-Label Classification Methods. CoRR abs/2102.07113 (2021) - [i17]Ana Kostovska, Diederick Vermetten, Carola Doerr, Saso Dzeroski, Pance Panov, Tome Eftimov:
OPTION: OPTImization Algorithm Benchmarking ONtology. CoRR abs/2104.11889 (2021) - [i16]Jasmin Bogatinovski, Ljupco Todorovski, Saso Dzeroski, Dragi Kocev:
Explaining the Performance of Multi-label Classification Methods with Data Set Properties. CoRR abs/2106.15411 (2021) - [i15]Ana Kostovska, Matej Petkovic, Tomaz Stepisnik, Luke Lucas, Timothy Finn, José Antonio Martínez Heras, Pance Panov, Saso Dzeroski, Alessandro Donati, Nikola Simidjievski, Dragi Kocev:
GalaxAI: Machine learning toolbox for interpretable analysis of spacecraft telemetry data. CoRR abs/2108.01407 (2021) - [i14]Urh Primozic, Blaz Skrlj, Saso Dzeroski, Matej Petkovic:
Unsupervised Feature Ranking via Attribute Networks. CoRR abs/2111.13273 (2021) - 2020
- [j96]Nikola Simidjievski, Ljupco Todorovski, Jus Kocijan, Saso Dzeroski:
Equation Discovery for Nonlinear System Identification. IEEE Access 8: 29930-29943 (2020) - [j95]Tomaz Stepisnik, Aljaz Osojnik, Saso Dzeroski, Dragi Kocev:
Option predictive clustering trees for multi-target regression. Comput. Sci. Inf. Syst. 17(2): 459-486 (2020) - [j94]Jovan Tanevski, Ljupco Todorovski, Saso Dzeroski:
Combinatorial search for selecting the structure of models of dynamical systems with equation discovery. Eng. Appl. Artif. Intell. 89: 103423 (2020) - [j93]Jurica Levatic, Michelangelo Ceci, Tomaz Stepisnik, Saso Dzeroski, Dragi Kocev:
Semi-supervised regression trees with application to QSAR modelling. Expert Syst. Appl. 158: 113569 (2020) - [j92]Matej Petkovic, Dragi Kocev, Saso Dzeroski:
Feature ranking for multi-target regression. Mach. Learn. 109(6): 1179-1204 (2020) - [j91]Aljaz Osojnik, Pance Panov, Saso Dzeroski:
Incremental predictive clustering trees for online semi-supervised multi-target regression. Mach. Learn. 109(11): 2121-2139 (2020) - [j90]Matej Petkovic, Saso Dzeroski, Dragi Kocev:
Multi-label feature ranking with ensemble methods. Mach. Learn. 109(11): 2141-2159 (2020) - [j89]Ivica Slavkov, Matej Petkovic, Pierre Geurts, Dragi Kocev, Saso Dzeroski:
Error curves for evaluating the quality of feature rankings. PeerJ Comput. Sci. 6: e310 (2020) - [j88]Maja Somrak, Saso Dzeroski, Ziga Kokalj:
Learning to Classify Structures in ALS-Derived Visualizations of Ancient Maya Settlements with CNN. Remote. Sens. 12(14): 2215 (2020) - [c158]Ilin Tolovski, Saso Dzeroski, Pance Panov:
Semantic Annotation of Predictive Modelling Experiments. DS 2020: 124-139 - [c157]Ana Kostovska, Saso Dzeroski, Pance Panov:
Semantic Description of Data Mining Datasets: An Ontology-Based Annotation Schema. DS 2020: 140-155 - [c156]Jure Brence, Jovan Tanevski, Jennifer Adams, Edward Malina, Saso Dzeroski:
Learning Surrogates of a Radiative Transfer Model for the Sentinel 5P Satellite. DS 2020: 217-230 - [c155]Vedrana Vidulin, Saso Dzeroski:
Hierarchy Decomposition Pipeline: A Toolbox for Comparison of Model Induction Algorithms on Hierarchical Multi-label Classification Problems. DS 2020: 486-501 - [c154]Blaz Skrlj, Saso Dzeroski, Nada Lavrac, Matej Petkovic:
Feature Importance Estimation with Self-Attention Networks. ECAI 2020: 1491-1498 - [c153]Matej Petkovic, Michelangelo Ceci, Kristian Kersting, Saso Dzeroski:
Estimating the Importance of Relational Features by Using Gradient Boosting. ISMIS 2020: 362-371 - [c152]Martin Breskvar, Saso Dzeroski:
Predicting Associations Between Proteins and Multiple Diseases. ISMIS 2020: 383-392 - [i13]Blaz Skrlj, Saso Dzeroski, Nada Lavrac, Matej Petkovic:
Feature Importance Estimation with Self-Attention Networks. CoRR abs/2002.04464 (2020) - [i12]Matej Mihelcic, Saso Dzeroski, Tomislav Smuc:
Multi-view redescription mining using tree-based multi-target prediction models. CoRR abs/2006.12227 (2020) - [i11]Matej Petkovic, Saso Dzeroski, Dragi Kocev:
Feature Ranking for Semi-supervised Learning. CoRR abs/2008.03937 (2020) - [i10]Matej Petkovic, Dragi Kocev, Blaz Skrlj, Saso Dzeroski:
Ensemble- and Distance-Based Feature Ranking for Unsupervised Learning. CoRR abs/2011.11679 (2020) - [i9]Jure Brence, Ljupco Todorovski, Saso Dzeroski:
Probabilistic Grammars for Equation Discovery. CoRR abs/2012.00428 (2020)
2010 – 2019
- 2019
- [j87]Franklin Parrales Bravo, Alberto A. Del Barrio García, Ana Beatriz Gago Veiga, María Mercedes Gallego de la Sacristana, Marina Ruiz Piñero, Angel Guerrero Peral, Saso Dzeroski, José L. Ayala:
SMURF: Systematic Methodology for Unveiling Relevant Factors in Retrospective Data on Chronic Disease Treatments. IEEE Access 7: 92598-92614 (2019) - [j86]Stevanche Nikoloski, Dragi Kocev, Saso Dzeroski:
Data-Driven Structuring of the Output Space Improves the Performance of Multi-Target Regressors. IEEE Access 7: 145177-145198 (2019) - [j85]Ziga Luksic, Jovan Tanevski, Saso Dzeroski, Ljupco Todorovski:
Meta-Model Framework for Surrogate-Based Parameter Estimation in Dynamical Systems. IEEE Access 7: 181829-181841 (2019) - [j84]Gjorgi Peev, Nikola Simidjievski, Saso Dzeroski:
Aiding the Task of Process-Based Modeling with ProBMoTViz. Int. J. Web Appl. 11(1): 27-38 (2019) - [c151]Aljaz Osojnik, Pance Panov, Saso Dzeroski:
Utilizing Hierarchies in Tree-Based Online Structured Output Prediction. DS 2019: 87-95 - [c150]Bozhidar Stevanoski, Dragi Kocev, Aljaz Osojnik, Ivica Dimitrovski, Saso Dzeroski:
Predicting Thermal Power Consumption of the Mars Express Satellite with Data Stream Mining. DS 2019: 186-201 - [c149]Matej Petkovic, Saso Dzeroski, Dragi Kocev:
Ensemble-Based Feature Ranking for Semi-supervised Classification. DS 2019: 290-305 - [c148]Ilin Tolovski, Ana Kostovska, Nikola Simidjievski, Ljupco Todorovski, Saso Dzeroski, Pance Panov:
Towards reusable process-based models of dynamical systems: A case study in the domain of aquatic ecosystems. MIPRO 2019: 1110-1115 - [e14]Petra Kralj Novak, Tomislav Smuc, Saso Dzeroski:
Discovery Science - 22nd International Conference, DS 2019, Split, Croatia, October 28-30, 2019, Proceedings. Lecture Notes in Computer Science 11828, Springer 2019, ISBN 978-3-030-33777-3 [contents] - [i8]Ziga Luksic, Jovan Tanevski, Saso Dzeroski, Ljupco Todorovski:
Meta-Model Framework for Surrogate-Based Parameter Estimation in Dynamical Systems. CoRR abs/1906.09088 (2019) - [i7]Nikola Simidjievski, Ljupco Todorovski, Jus Kocijan, Saso Dzeroski:
Equation Discovery for Nonlinear System Identification. CoRR abs/1907.00821 (2019) - 2018
- [j83]Ivica Slavkov, Jana Karcheska, Dragi Kocev, Saso Dzeroski:
HMC-ReliefF: Feature ranking for hierarchical multi-label classification. Comput. Sci. Inf. Syst. 15(1): 187-209 (2018) - [j82]Ivica Slavkov, Matej Petkovic, Dragi Kocev, Saso Dzeroski:
Quantitative Score for Assessing the Quality of Feature Rankings. Informatica (Slovenia) 42(1) (2018) - [j81]Jurica Levatic, Dragi Kocev, Michelangelo Ceci, Saso Dzeroski:
Semi-supervised trees for multi-target regression. Inf. Sci. 450: 109-127 (2018) - [j80]Matej Mihelcic, Saso Dzeroski, Nada Lavrac, Tomislav Smuc:
Redescription mining augmented with random forest of multi-target predictive clustering trees. J. Intell. Inf. Syst. 50(1): 63-96 (2018) - [j79]Aljaz Osojnik, Pance Panov, Saso Dzeroski:
Tree-based methods for online multi-target regression. J. Intell. Inf. Syst. 50(2): 315-339 (2018) - [j78]Martin Breskvar, Dragi Kocev, Saso Dzeroski:
Ensembles for multi-target regression with random output selections. Mach. Learn. 107(11): 1673-1709 (2018) - [c147]Matej Petkovic, Dragi Kocev, Saso Dzeroski:
Feature Ranking with Relief for Multi-label Classification: Does Distance Matter? DS 2018: 51-65 - [c146]Matej Mihelcic, Saso Dzeroski, Tomislav Smuc:
Extending Redescription Mining to Multiple Views. DS 2018: 292-307 - [c145]Jihed Khiari, Luís Moreira-Matias, Ammar Shaker, Bernard Zenko, Saso Dzeroski:
MetaBags: Bagged Meta-Decision Trees for Regression. ECML/PKDD (1) 2018: 637-652 - [i6]Jihed Khiari, Luís Moreira-Matias, Ammar Shaker, Bernard Zenko, Saso Dzeroski:
MetaBags: Bagged Meta-Decision Trees for Regression. CoRR abs/1804.06207 (2018) - [i5]Matej Petkovic, Redouane Boumghar, Martin Breskvar, Saso Dzeroski, Dragi Kocev, Jurica Levatic, Luke Lucas, Aljaz Osojnik, Bernard Zenko, Nikola Simidjievski:
Machine learning for predicting thermal power consumption of the Mars Express Spacecraft. CoRR abs/1809.00542 (2018) - 2017
- [j77]Matej Mihelcic, Saso Dzeroski, Nada Lavrac, Tomislav Smuc:
A framework for redescription set construction. Expert Syst. Appl. 68: 196-215 (2017) - [j76]Gjorgji Madjarov, Dejan Gjorgjevikj, Ivica Dimitrovski, Saso Dzeroski:
Erratum to: The use of data-derived label hierarchies in multi-label classification. J. Intell. Inf. Syst. 48(2): 475-476 (2017) - [j75]