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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]Jurica Levatic, Michelangelo Ceci, Dragi Kocev, Saso Dzeroski:
Semi-supervised classification trees. J. Intell. Inf. Syst. 49(3): 461-486 (2017) - [j74]Jurica Levatic, Michelangelo Ceci, Dragi Kocev, Saso Dzeroski:
Self-training for multi-target regression with tree ensembles. Knowl. Based Syst. 123: 41-60 (2017) - [j73]Aljaz Osojnik, Pance Panov, Saso Dzeroski:
Multi-label classification via multi-target regression on data streams. Mach. Learn. 106(6): 745-770 (2017) - [c144]Mate Bestek, Dragi Kocev, Saso Dzeroski, Andrej Brodnik, Rade Iljaz:
Modelling Time-Series of Glucose Measurements from Diabetes Patients Using Predictive Clustering Trees. AIME 2017: 95-104 - [c143]Ziga Luksic, Jovan Tanevski, Saso Dzeroski, Ljupco Todorovski:
General Meta-Model Framework for Surrogate-Based Numerical Optimization. DS 2017: 51-66 - [c142]Martin Breskvar, Dragi Kocev, Saso Dzeroski:
Multi-label Classification Using Random Label Subset Selections. DS 2017: 108-115 - [c141]Tomaz Stepisnik Perdih, Aljaz Osojnik, Saso Dzeroski, Dragi Kocev:
Option Predictive Clustering Trees for Hierarchical Multi-label Classification. DS 2017: 116-123 - [c140]Matej Petkovic, Saso Dzeroski, Dragi Kocev:
Feature Ranking for Multi-target Regression with Tree Ensemble Methods. DS 2017: 171-185 - [c139]Valentin Gjorgjioski, Dragi Kocev, Andrej Boncina, Saso Dzeroski, Marko Debeljak:
Predictive Clustering of Multi-dimensional Time Series Applied to Forest Growing Stock Data for Different Tree Sizes. ICT Innovations 2017: 186-195 - [c138]Vanja Mileski, Saso Dzeroski, Dragi Kocev:
Predictive Clustering Trees for Hierarchical Multi-Target Regression. IDA 2017: 223-234 - [c137]Jurica Levatic, Maria Brbic, Tomaz Stepisnik Perdih, Dragi Kocev, Vedrana Vidulin, Tomislav Smuc, Fran Supek, Saso Dzeroski:
Phenotype Prediction with Semi-supervised Classification Trees. NFMCP@PKDD/ECML 2017: 138-150 - [c136]Stevanche Nikoloski, Dragi Kocev, Saso Dzeroski:
Structuring the Output Space in Multi-label Classification by Using Feature Ranking. NFMCP@PKDD/ECML 2017: 151-166 - [c135]Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, Saso Dzeroski:
Image Representation, Annotation and Retrieval with Predictive Clustering Trees. ECML/PKDD (3) 2017: 363-367 - [c134]Jovan Tanevski, Nikola Simidjievski, Ljupco Todorovski, Saso Dzeroski:
Process-Based Modeling and Design of Dynamical Systems. ECML/PKDD (3) 2017: 378-382 - [e13]Michelangelo Ceci, Jaakko Hollmén, Ljupco Todorovski, Celine Vens, Saso Dzeroski:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part I. Lecture Notes in Computer Science 10534, Springer 2017, ISBN 978-3-319-71248-2 [contents] - [e12]Michelangelo Ceci, Jaakko Hollmén, Ljupco Todorovski, Celine Vens, Saso Dzeroski:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part II. Lecture Notes in Computer Science 10535, Springer 2017, ISBN 978-3-319-71245-1 [contents] - [e11]Yasemin Altun, Kamalika Das, Taneli Mielikäinen, Donato Malerba, Jerzy Stefanowski, Jesse Read, Marinka Zitnik, Michelangelo Ceci, Saso Dzeroski:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part III. Lecture Notes in Computer Science 10536, Springer 2017, ISBN 978-3-319-71272-7 [contents] - [i4]Matej Mihelcic, Goran Simic, Mirjana Babic Leko, Nada Lavrac, Saso Dzeroski, Tomislav Smuc:
Using Redescription Mining to Relate Clinical and Biological Characteristics of Cognitively Impaired and Alzheimer's Disease Patients. CoRR abs/1702.06831 (2017) - [i3]Nikola Simidjievski, Jovan Tanevski, Bernard Zenko, Zoran Levnajic, Ljupco Todorovski, Saso Dzeroski:
Decoupling approximation robustly reconstructs directed dynamical networks. CoRR abs/1712.03100 (2017) - 2016
- [j72]Jovan Tanevski, Ljupco Todorovski, Saso Dzeroski:
Learning stochastic process-based models of dynamical systems from knowledge and data. BMC Syst. Biol. 10: 30 (2016) - [j71]Aljaz Osojnik, Pance Panov, Saso Dzeroski:
Modeling dynamical systems with data stream mining. Comput. Sci. Inf. Syst. 13(2): 453-473 (2016) - [j70]Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, Saso Dzeroski:
Improving bag-of-visual-words image retrieval with predictive clustering trees. Inf. Sci. 329: 851-865 (2016) - [j69]Pance Panov, Larisa N. Soldatova, Saso Dzeroski:
Generic ontology of datatypes. Inf. Sci. 329: 900-920 (2016) - [j68]Gjorgji Madjarov, Dejan Gjorgjevikj, Ivica Dimitrovski, Saso Dzeroski:
The use of data-derived label hierarchies in multi-label classification. J. Intell. Inf. Syst. 47(1): 57-90 (2016) - [j67]Saso Dzeroski, Dragi Kocev, Pance Panov:
Special issue on discovery science. Mach. Learn. 105(1): 1-2 (2016) - [j66]Darko Aleksovski, Jus Kocijan, Saso Dzeroski:
Ensembles of Fuzzy Linear Model Trees for the Identification of Multioutput Systems. IEEE Trans. Fuzzy Syst. 24(4): 916-929 (2016) - [c133]Aljaz Osojnik, Saso Dzeroski, Dragi Kocev:
Option Predictive Clustering Trees for Multi-target Regression. DS 2016: 118-133 - [c132]Nikola Simidjievski, Ljupco Todorovski, Saso Dzeroski:
Learning Ensembles of Process-Based Models by Bagging of Random Library Samples. DS 2016: 245-260 - [c131]Matej Petkovic, Pance Panov, Saso Dzeroski:
A Comparison of Different Data Transformation Approaches in the Feature Ranking Context. DS 2016: 310-324 - [c130]Saso Dzeroski:
Learning from Massive, Incompletely annotated & Structured Data. EGC 2016: 7-8 - [c129]Michelangelo Ceci, Gianvito Pio, Vladimir Kuzmanovski, Saso Dzeroski:
Semi-Supervised Multi-View Learning for Gene Network Reconstruction. SEBD 2016: 198-205 - [c128]Agnieszka Lawrynowicz, Diego Esteves, Pance Panov, Tommaso Soru, Saso Dzeroski, Joaquin Vanschoren:
An Algorithm, Implementation and Execution Ontology Design Pattern. WOP@ISWC 2016: 55-68 - [i2]Matej Mihelcic, Saso Dzeroski, Nada Lavrac, Tomislav Smuc:
A framework for redescription set construction. CoRR abs/1606.03935 (2016) - 2015
- [j65]Darko Aleksovski, Jus Kocijan, Saso Dzeroski:
Model-Tree Ensembles for noise-tolerant system identification. Adv. Eng. Informatics 29(1): 1-15 (2015) - [j64]Jovan Tanevski, Ljupco Todorovski, Yannis Kalaidzidis, Saso Dzeroski:
Domain-specific model selection for structural identification of the Rab5-Rab7 dynamics in endocytosis. BMC Syst. Biol. 9: 31 (2015) - [j63]Ivica Dimitrovski, Dragi Kocev, Ivan Kitanovski, Suzana Loskovska, Saso Dzeroski:
Improved medical image modality classification using a combination of visual and textual features. Comput. Medical Imaging Graph. 39: 14-26 (2015) - [j62]Nikola Simidjievski, Ljupco Todorovski, Saso Dzeroski:
Predicting long-term population dynamics with bagging and boosting of process-based models. Expert Syst. Appl. 42(22): 8484-8496 (2015) - [j61]Elena Ikonomovska, João Gama, Saso Dzeroski:
Online tree-based ensembles and option trees for regression on evolving data streams. Neurocomputing 150: 458-470 (2015) - [j60]Jurica Levatic, Dragi Kocev, Saso Dzeroski:
The importance of the label hierarchy in hierarchical multi-label classification. J. Intell. Inf. Syst. 45(2): 247-271 (2015) - [c127]Aljaz Osojnik, Pance Panov, Saso Dzeroski:
Multi-label Classification via Multi-target Regression on Data Streams. Discovery Science 2015: 170-185 - [c126]Pance Panov, Larisa N. Soldatova, Saso Dzeroski:
Representing bioinformatics datatypes using the OntoDT ontology. ICBO 2015 - [c125]Larisa N. Soldatova, Pance Panov, Saso Dzeroski:
Ontology Engineering: From an Art to a Craft - The Case of the Data Mining Ontologies. OWLED 2015: 174-181 - [c124]Aljaz Osojnik, Pance Panov, Saso Dzeroski:
Comparison of Tree-Based Methods for Multi-target Regression on Data Streams. NFMCP 2015: 17-31 - [c123]Matej Mihelcic, Saso Dzeroski, Nada Lavrac, Tomislav Smuc:
Redescription Mining with Multi-target Predictive Clustering Trees. NFMCP 2015: 125-143 - [c122]Jurica Levatic, Michelangelo Ceci, Dragi Kocev, Saso Dzeroski:
Semi-supervised learning for multi-target regression (Discussion paper). SEBD 2015: 240-247 - 2014
- [j59]Pance Panov, Larisa N. Soldatova, Saso Dzeroski:
Ontology of core data mining entities. Data Min. Knowl. Discov. 28(5-6): 1222-1265 (2014) - [j58]Mateja Skerjanec, Natasa Atanasova, Darko Cerepnalkoski, Saso Dzeroski, Boris Kompare:
Development of a knowledge library for automated watershed modeling. Environ. Model. Softw. 54: 60-72 (2014) - [j57]Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, Saso Dzeroski:
Fast and efficient visual codebook construction for multi-label annotation using predictive clustering trees. Pattern Recognit. Lett. 38: 38-45 (2014) - [c121]Rok Piltaver, Mitja Lustrek, Jernej Zupancic, Saso Dzeroski, Matjaz Gams:
Multi-objective learning of hybrid classifiers. ECAI 2014: 717-722 - [c120]Darko Aleksovski, Jus Kocijan, Saso Dzeroski:
Model Tree Ensembles for the Identification of Multiple-Output Systems. ECC 2014: 750-755 - [c119]Jurica Levatic, Michelangelo Ceci, Dragi Kocev, Saso Dzeroski:
Semi-supervised Learning for Multi-target Regression. NFMCP 2014: 3-18 - [c118]Gjorgji Madjarov, Ivica Dimitrovski, Dejan Gjorgjevikj, Saso Dzeroski:
Evaluation of Different Data-Derived Label Hierarchies in Multi-label Classification. NFMCP 2014: 19-37 - [e10]Saso Dzeroski, Pance Panov, Dragi Kocev, Ljupco Todorovski:
Discovery Science - 17th International Conference, DS 2014, Bled, Slovenia, October 8-10, 2014. Proceedings. Lecture Notes in Computer Science 8777, Springer 2014, ISBN 978-3-319-11811-6 [contents] - 2013
- [j56]Daniela Stojanova, Michelangelo Ceci, Donato Malerba, Saso Dzeroski:
Using PPI network autocorrelation in hierarchical multi-label classification trees for gene function prediction. BMC Bioinform. 14: 285 (2013) - [j55]Daniela Stojanova, Michelangelo Ceci, Annalisa Appice, Donato Malerba, Saso Dzeroski:
Dealing with spatial autocorrelation when learning predictive clustering trees. Ecol. Informatics 13: 22-39 (2013) - [j54]Dragi Kocev, Saso Dzeroski:
Habitat modeling with single- and multi-target trees and ensembles. Ecol. Informatics 18: 79-92 (2013) - [j53]Dejan Gjorgjevikj, Gjorgji Madjarov, Saso Dzeroski:
Hybrid Decision Tree Architecture Utilizing Local SVMs for Efficient Multi-Label Learning. Int. J. Pattern Recognit. Artif. Intell. 27(7) (2013) - [j52]Jurica Levatic, Saso Dzeroski, Fran Supek, Tomislav Smuc:
Semi-Supervised Learning for Quantitative Structure-Activity Modeling. Informatica (Slovenia) 37(2): 173-179 (2013) - [j51]Nives Skunca, Matko Bosnjak, Anita Krisko, Pance Panov, Saso Dzeroski, Tomislav Smuc, Fran Supek:
Phyletic Profiling with Cliques of Orthologs Is Enhanced by Signatures of Paralogy Relationships. PLoS Comput. Biol. 9(1) (2013) - [j50]Dragi Kocev, Celine Vens, Jan Struyf, Saso Dzeroski:
Tree ensembles for predicting structured outputs. Pattern Recognit. 46(3): 817-833 (2013) - [c117]Darko Aleksovski, Jus Kocijan, Saso Dzeroski:
Model Tree Ensembles for Modeling Dynamic Systems. Discovery Science 2013: 17-32 - [c116]Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, Saso Dzeroski:
Fast and Scalable Image Retrieval Using Predictive Clustering Trees. Discovery Science 2013: 33-48 - [c115]Pance Panov, Larisa N. Soldatova, Saso Dzeroski:
OntoDM-KDD: Ontology for Representing the Knowledge Discovery Process. Discovery Science 2013: 126-140 - [c114]Daniela Stojanova, Michelangelo Ceci, Donato Malerba, Saso Dzeroski:
Learning Hierarchical Multi-label Classification Trees from Network Data. Discovery Science 2013: 233-248 - [c113]Jovan Tanevski, Ljupco Todorovski, Yannis Kalaidzidis, Saso Dzeroski:
Inductive Process Modeling of Rab5-Rab7 Conversion in Endocytosis. Discovery Science 2013: 265-280 - [c112]Ivica Slavkov, Jana Karcheska, Dragi Kocev, Slobodan Kalajdziski, Saso Dzeroski:
ReliefF for Hierarchical Multi-label Classification. NFMCP 2013: 148-161 - [c111]Jurica Levatic, Dragi Kocev, Saso Dzeroski:
The Use of the Label Hierarchy in Hierarchical Multi-label Classification Improves Performance. NFMCP 2013: 162-177 - 2012
- [j49]Daniela Stojanova, Andrej Kobler, Peter Ogrinc, Bernard Zenko, Saso Dzeroski:
Estimating the risk of fire outbreaks in the natural environment. Data Min. Knowl. Discov. 24(2): 411-442 (2012) - [j48]Daniela Stojanova, Michelangelo Ceci, Annalisa Appice, Saso Dzeroski:
Network regression with predictive clustering trees. Data Min. Knowl. Discov. 25(2): 378-413 (2012) - [j47]Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, Saso Dzeroski:
Hierarchical classification of diatom images using ensembles of predictive clustering trees. Ecol. Informatics 7(1): 19-29 (2012) - [j46]Timo Aho, Bernard Zenko, Saso Dzeroski, Tapio Elomaa:
Multi-target regression with rule ensembles. J. Mach. Learn. Res. 13: 2367-2407 (2012) - [j45]Gjorgji Madjarov, Dejan Gjorgjevikj, Saso Dzeroski:
Two stage architecture for multi-label learning. Pattern Recognit. 45(3): 1019-1034 (2012) - [j44]Gjorgji Madjarov, Dragi Kocev, Dejan Gjorgjevikj, Saso Dzeroski:
An extensive experimental comparison of methods for multi-label learning. Pattern Recognit. 45(9): 3084-3104 (2012) - 2011
- [j43]Katerina Tashkova, Peter Korosec, Jurij Silc, Ljupco Todorovski, Saso Dzeroski:
Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis. BMC Syst. Biol. 5: 159 (2011) - [j42]Elena Ikonomovska, João Gama, Saso Dzeroski:
Learning model trees from evolving data streams. Data Min. Knowl. Discov. 23(1): 128-168 (2011) - [j41]Natasa Atanasova, Saso Dzeroski, Boris Kompare, Ljupco Todorovski, Gideon Gal:
Automated discovery of a model for dinoflagellate dynamics. Environ. Model. Softw. 26(5): 658-668 (2011) - [j40]Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, Saso Dzeroski:
Hierarchical annotation of medical images. Pattern Recognit. 44(10-11): 2436-2449 (2011) - [c110]Mitja Pugelj, Saso Dzeroski:
Predicting Structured Outputs k-Nearest Neighbours Method. Discovery Science 2011: 262-276 - [c109]Daniela Stojanova, Michelangelo Ceci, Annalisa Appice, Donato Malerba, Saso Dzeroski:
Global and Local Spatial Autocorrelation in Predictive Clustering Trees. Discovery Science 2011: 307-322 - [c108]Elena Ikonomovska, Saso Dzeroski:
Regression on evolving multi-relational data streams. EDBT/ICDT Ph.D. Workshop 2011: 1-7 - [c107]Gjorgji Madjarov, Dejan Gjorgjevikj, Saso Dzeroski:
Dual Layer Voting Method for Efficient Multi-label Classification. IbPRIA 2011: 232-239 - [c106]Elena Ikonomovska, Kurt Driessens, Saso Dzeroski, João Gama:
Adaptive Windowing for Online Learning from Multiple Inter-related Data Streams. ICDM Workshops 2011: 697-704 - [c105]Saso Dzeroski:
Inductive Databases and Constraint-Based Data Mining. ICFCA 2011: 1-17 - [c104]Elena Ikonomovska, João Gama, Bernard Zenko, Saso Dzeroski:
Speeding-Up Hoeffding-Based Regression Trees With Options. ICML 2011: 537-544 - [c103]Daniela Stojanova, Michelangelo Ceci, Annalisa Appice, Saso Dzeroski:
Network Regression with Predictive Clustering Trees. ECML/PKDD (3) 2011: 333-348 - [c102]Elena Ikonomovska, João Gama, Saso Dzeroski:
Incremental multi-target model trees for data streams. SAC 2011: 988-993 - 2010
- [j39]Leander Schietgat, Celine Vens, Jan Struyf, Hendrik Blockeel, Dragi Kocev, Saso Dzeroski:
Predicting gene function using hierarchical multi-label decision tree ensembles. BMC Bioinform. 11: 2 (2010) - [j38]Daniela Stojanova, Pance Panov, Valentin Gjorgjioski, Andrej Kobler, Saso Dzeroski:
Estimating vegetation height and canopy cover from remotely sensed data with machine learning. Ecol. Informatics 5(4): 256-266 (2010) - [c101]Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, Saso Dzeroski:
Detection of Visual Concepts and Annotation of Images Using Predictive Clustering Trees. CLEF (Notebook Papers/LABs/Workshops) 2010 - [c100]Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, Saso Dzeroski:
Detection of Visual Concepts and Annotation of Images Using Ensembles of Trees for Hierarchical Multi-Label Classification. ICPR Contests 2010: 152-161 - [c99]Saso Dzeroski, Pierre Geurts, Juho Rousu:
Preface. MLSB 2010: 1-2 - [c98]Ivica Slavkov, Bernard Zenko, Saso Dzeroski:
Evaluation Method for Feature Rankings and their Aggregations for Biomarker Discovery. MLSB 2010: 122-135 - [p11]Saso Dzeroski:
Inductive Databases and Constraint-based Data Mining: Introduction and Overview. Inductive Databases and Constraint-Based Data Mining 2010: 3-26 - [p10]Pance Panov, Saso Dzeroski, Larisa N. Soldatova:
Representing Entities in the OntoDM Data Mining Ontology. Inductive Databases and Constraint-Based Data Mining 2010: 27-58 - [p9]Jan Struyf, Saso Dzeroski:
Constrained Predictive Clustering. Inductive Databases and Constraint-Based Data Mining 2010: 155-175 - [p8]Celine Vens, Leander Schietgat, Jan Struyf, Hendrik Blockeel, Dragi Kocev, Saso Dzeroski:
Predicting Gene Function using Predictive Clustering Trees. Inductive Databases and Constraint-Based Data Mining 2010: 365-387 - [p7]Ivica Slavkov, Saso Dzeroski:
Analyzing Gene Expression Data with Predictive Clustering Trees. Inductive Databases and Constraint-Based Data Mining 2010: 389-406 - [p6]Saso Dzeroski:
Relational Data Mining. Data Mining and Knowledge Discovery Handbook 2010: 887-911 - [e9]Saso Dzeroski, Bart Goethals, Pance Panov:
Inductive Databases and Constraint-Based Data Mining. Springer 2010, ISBN 978-1-4419-7737-3 [contents] - [e8]Saso Dzeroski, Pierre Geurts, Juho Rousu:
Proceedings of the third International Workshop on Machine Learning in Systems Biology, MLSB 2009, Ljubljana, Slovenia, September 5-6, 2009. JMLR Proceedings 8, JMLR.org 2010 [contents]
2000 – 2009
- 2009
- [c97]Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, Saso Dzeroski:
ImageCLEF 2009 Medical Image Annotation Task: PCTs for Hierarchical Multi-Label Classification. CLEF (2) 2009: 231-238 - [c96]Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, Saso Dzeroski:
ImageCLEF 2009 Medical Image Annotation Task: PCTs for Hierarchical Multi-Label Classification. CLEF (Working Notes) 2009 - [c95]Pance Panov, Larisa N. Soldatova, Saso Dzeroski:
Towards an Ontology of Data Mining Investigations. Discovery Science 2009: 257-271 - [c94]Timo Aho, Bernard Zenko, Saso Dzeroski:
Rule Ensembles for Multi-target Regression. ICDM 2009: 21-30 - [c93]Andreja Naumoski, Dragi Kocev, Natasa Atanasova, Kosta Mitreski, Svetislav Krstic, Saso Dzeroski:
Predicting chemical parameters of the water from diatom abudance in lake Prespa and its tributaries. ITEE 2009: 264-277 - [r1]Saso Dzeroski, Pance Panov, Bernard Zenko:
Machine Learning, Ensemble Methods in. Encyclopedia of Complexity and Systems Science 2009: 5317-5325 - 2008
- [j37]Will Bridewell, Pat Langley, Ljupco Todorovski, Saso Dzeroski:
Inductive process modeling. Mach. Learn. 71(1): 1-32 (2008) - [j36]Celine Vens, Jan Struyf, Leander Schietgat, Saso Dzeroski, Hendrik Blockeel:
Decision trees for hierarchical multi-label classification. Mach. Learn. 73(2): 185-214 (2008) - [c92]Pance Panov, Saso Dzeroski, Larisa N. Soldatova:
OntoDM: An Ontology of Data Mining. ICDM Workshops 2008: 752-760 - [c91]Aleksandar Peckov, Saso Dzeroski, Ljupco Todorovski:
A Minimal Description Length Scheme for Polynomial Regression. PAKDD 2008: 284-295 - [c90]Bernard Zenko, Saso Dzeroski:
Learning Classification Rules for Multiple Target Attributes. PAKDD 2008: 454-465 - 2007
- [j35]Katerina Taskova, Daniela Stojanova, Marko Bohanec, Saso Dzeroski:
A Qualitative Decision-Support Model for Evaluating Researchers. Informatica (Slovenia) 31(4): 479-486 (2007) - [j34]Saso Dzeroski, Jan Struyf:
5th international workshop on knowledge discovery in inductive databases (KDID'06): workshop report. SIGKDD Explor. 9(1): 56-58 (2007) - [c89]Jan Struyf, Saso Dzeroski:
Clustering Trees with Instance Level Constraints. ECML 2007: 359-370 - [c88]Annalisa Appice, Saso Dzeroski:
Stepwise Induction of Multi-target Model Trees. ECML 2007: 502-509 - [c87]Dragi Kocev, Celine Vens, Jan Struyf, Saso Dzeroski:
Ensembles of Multi-Objective Decision Trees. ECML 2007: 624-631 - [c86]Aneta Ivanovska, Celine Vens, Saso Dzeroski, Nathalie Colbach:
Studying the Presence of Genetically Modified Variants in Organic Oilseed Rape by Using Relational Data Mining. EnviroInfo (1) 2007: 417-424 - [c85]Pance Panov, Saso Dzeroski:
Combining Bagging and Random Subspaces to Create Better Ensembles. IDA 2007: 118-129 - [c84]Annalisa Appice, Saso Dzeroski:
Inducing Multi-Target Model Trees in a Stepwise Fashion. SEBD 2007: 16-27 - [p5]Saso Dzeroski, Pat Langley, Ljupco Todorovski:
Computational Discovery of Scientific Knowledge. Computational Discovery of Scientific Knowledge 2007: 1-14 - [p4]Ljupco Todorovski, Saso Dzeroski:
Integrating Domain Knowledge in Equation Discovery. Computational Discovery of Scientific Knowledge 2007: 69-97 - [p3]Dimitar Hristovski, Borut Peterlin, Saso Dzeroski, Janez Stare:
Literature Based Discovery Support System and Its Application to Disease Gene Identification. Computational Discovery of Scientific Knowledge 2007: 307-326 - [e7]Saso Dzeroski, Ljupco Todorovski:
Computational Discovery of Scientific Knowledge, Introduction, Techniques, and Applications in Environmental and Life Sciences. Lecture Notes in Computer Science 4660, Springer 2007, ISBN 978-3-540-73919-7 [contents] - [e6]Saso Dzeroski, Jan Struyf:
Knowledge Discovery in Inductive Databases, 5th International Workshop, KDID 2006, Berlin, Germany, September 18, 2006, Revised Selected and Invited Papers. Lecture Notes in Computer Science 4747, Springer 2007, ISBN 978-3-540-75548-7 [contents] - 2006
- [j33]Anneleen Van Assche, Celine Vens, Hendrik Blockeel, Saso Dzeroski:
First order random forests: Learning relational classifiers with complex aggregates. Mach. Learn. 64(1-3): 149-182 (2006) - [c83]Taneli Mielikäinen, Pance Panov, Saso Dzeroski:
Itemset Support Queries Using Frequent Itemsets and Their Condensed Representations. Discovery Science 2006: 161-172 - [c82]Saso Dzeroski, Andrej Kobler, Valentin Gjorgjioski, Pance Panov:
Using Decision Trees to Predict Forest Stand Height and Canopy Cover from LANDSAT and LIDAR Data. EnviroInfo 2006: 125-133 - [c81]Damjan Demsar, Saso Dzeroski, Marko Debeljak, Paul Henning Krogh:
Predicting Aggregate Properties of Soil Communities vs. Community Structure in an Agricultural Setting. EnviroInfo 2006: 295-302 - [c80]Aneta Ivanovska, Pance Panov, Nathalie Colbach, Marko Debeljak, Saso Dzeroski, Antoine Messéan:
Using Simulation Models and Data Mining to Study Co-Existence of GM/Non-GM Crops at Regional Level. EnviroInfo 2006: 493-500 - [c79]Saso Dzeroski:
From Inductive Logic Programming to Relational Data Mining. JELIA 2006: 1-14 - [c78]Saso Dzeroski, Valentin Gjorgjioski, Ivica Slavkov, Jan Struyf:
Analysis of Time Series Data with Predictive Clustering Trees. KDID 2006: 63-80 - [c77]Dragi Kocev, Jan Struyf, Saso Dzeroski:
Beam Search Induction and Similarity Constraints for Predictive Clustering Trees. KDID 2006: 134-151 - [c76]Saso Dzeroski:
Towards a General Framework for Data Mining. KDID 2006: 259-300 - [c75]Saso Dzeroski, Tomaz Erjavec, Nina Ledinek, Petr Pajas, Zdenek Zabokrtský, Anreja Zele:
Towards a Slovene Dependency Treebank. LREC 2006: 1388-1391 - [c74]Hendrik Blockeel, Leander Schietgat, Jan Struyf, Saso Dzeroski, Amanda Clare:
Decision Trees for Hierarchical Multilabel Classification: A Case Study in Functional Genomics. PKDD 2006: 18-29 - 2005
- [j32]Hendrik Blockeel, Saso Dzeroski:
Multi-Relational Data Mining 2005: workshop report. SIGKDD Explor. 7(2): 126-128 (2005) - [c73]Kurt Driessens, Saso Dzeroski:
Combining Model-Based and Instance-Based Learning for First Order Regression. BNAIC 2005: 341-342 - [c72]Marko Debeljak, Damjan Demsar, Saso Dzeroski, Joachim Schiemann, Ralf Wilhelm, Sara Meier-Bethke:
Modelling Outcrossing of Transgenes in Maize Between Neighboring Maize Fields. EnviroInfo 2005: 610-614 - [c71]Marko Debeljak, Jérôme Cortet, Damjan Demsar, Saso Dzeroski:
Using Data Mining to Assess the Effects of Bt Baize on Soil Microarthropods. EnviroInfo 2005: 615-620 - [c70]Marko Bohanec, Antoine Messéan, Sara Scatasta, Saso Dzeroski, Martin Znidarsic:
A Qualitative Multi-attribute Model for Economic and Ecological Evaluation of Genetically Modified Crops. EnviroInfo 2005: 661-668 - [c69]Jan Struyf, Saso Dzeroski, Hendrik Blockeel, Amanda Clare:
Hierarchical Multi-classification with Predictive Clustering Trees in Functional Genomics. EPIA 2005: 272-283 - [c68]Kurt Driessens, Saso Dzeroski:
Combining model-based and instance-based learning for first order regression. ICML 2005: 193-200 - [c67]Jan Struyf, Saso Dzeroski:
Constraint Based Induction of Multi-objective Regression Trees. KDID 2005: 222-233 - [c66]Bernard Zenko, Saso Dzeroski, Jan Struyf:
Learning Predictive Clustering Rules. KDID 2005: 234-250 - [p2]Saso Dzeroski:
Relational Data Mining. The Data Mining and Knowledge Discovery Handbook 2005: 869-898 - 2004
- [j31]Tomaz Erjavec, Saso Dzeroski:
Machine Learning of Morphosyntactic Structure: Lemmatizing Unknown Slovene Words. Appl. Artif. Intell. 18(1): 17-41 (2004) - [j30]Hendrik Blockeel, Saso Dzeroski, Boris Kompare, Stefan Kramer, Bernhard Pfahringer, Wim Van Laer:
Experiments In Predicting Biodegradability. Appl. Artif. Intell. 18(2): 157-181 (2004) - [j29]Marko Bohanec, Saso Dzeroski, Martin Znidarsic:
Multi-Attribute Modelling of Economic and Ecological Impacts of Cropping Systems. Informatica (Slovenia) 28(4): 387-392 (2004) - [j28]Saso Dzeroski, Bernard Zenko:
Is Combining Classifiers with Stacking Better than Selecting the Best One? Mach. Learn. 54(3): 255-273 (2004) - [j27]Kurt Driessens, Saso Dzeroski:
Integrating Guidance into Relational Reinforcement Learning. Mach. Learn. 57(3): 271-304 (2004) - [j26]Saso Dzeroski, Hendrik Blockeel:
Multi-relational data mining 2004: workshop report. SIGKDD Explor. 6(2): 140-141 (2004) - [j25]Saso Dzeroski, Bernard Zenko, Marko Debeljak:
A report on the fourth international workshop on environmental applications of machine learning (EAML 2004). SIGKDD Explor. 6(2): 155-156 (2004) - [c65]Saso Dzeroski, Ljupco Todorovski, Peter Ljubic:
Inductive Queries on Polynomial Equations. Constraint-Based Mining and Inductive Databases 2004: 127-154 - [c64]Nada Lavrac, Filip Zelezný, Saso Dzeroski:
Local Patterns: Theory and Practice of Constraint-Based Relational Subgroup Discovery. Local Pattern Detection 2004: 71-88 - [c63]Saso Dzeroski, Ljupco Todorovski, Peter Ljubic:
Inductive Databases of Polynomial Equations. DaWaK 2004: 159-168 - [c62]Ljupco Todorovski, Peter Ljubic, Saso Dzeroski:
Inducing Polynomial Equations for Regression. ECML 2004: 441-452 - [c61]Damjan Demsar, Saso Dzeroski, Paul Henning Krogh, Thomas Larsen:
Discovering the most important factors for communities of soil microarthropods using machine learning. EnviroInfo (1) 2004: 194-204 - [c60]Ljupco Todorovski, Saso Dzeroski:
Integrating Knowledge-Driven and Data-Driven Approaches to Modeling. EnviroInfo (1) 2004: 215-226 - [c59]Bernard Zenko, Saso Dzeroski, Alfred B. Kobal, Darja Kobal Grum, Niko Arneri, Josko Osredkar, Milena Horvat:
Relating personality traits and mercury exposure in miners with machine learning methods. EnviroInfo (1) 2004: 400-412 - [c58]Celine Vens, Anneleen Van Assche, Hendrik Blockeel, Saso Dzeroski:
First Order Random Forests with Complex Aggregates. ILP 2004: 323-340 - [i1]Raghu Ramakrishnan, Rakesh Agrawal, Johann-Christoph Freytag, Toni Bollinger, Christopher W. Clifton, Saso Dzeroski, Jochen Hipp, Daniel A. Keim, Stefan Kramer, Hans-Peter Kriegel, Ulf Leser, Bing Liu, Heikki Mannila, Rosa Meo, Shinichi Morishita, Raymond T. Ng, Jian Pei, Prabhakar Raghavan, Myra Spiliopoulou, Jaideep Srivastava, Vicenç Torra:
Data Mining: The Next Generation. Perspectives Workshop: Data Mining: The Next Generation 2004 - 2003
- [j24]Ljupco Todorovski, Saso Dzeroski:
Combining Classifiers with Meta Decision Trees. Mach. Learn. 50(3): 223-249 (2003) - [j23]Saso Dzeroski:
Multi-relational data mining: an introduction. SIGKDD Explor. 5(1): 1-16 (2003) - [j22]Saso Dzeroski, Luc De Raedt:
Multi-relational data mining: the current frontiers. SIGKDD Explor. 5(1): 100-101 (2003) - [j21]Saso Dzeroski, Luc De Raedt, Stefan Wrobel:
Multirelational data mining 2003: workshop report. SIGKDD Explor. 5(2): 200-202 (2003) - [c57]Saso Dzeroski, Ljupco Todorovski, Boris Zmazek, Janja Vaupotic, Ivan Kobal:
Modelling Soil Radon Concentration for Earthquake Prediction. Discovery Science 2003: 87-99 - [c56]Saso Dzeroski, Ljupco Todorovski, Peter Ljubic:
Using Constraints in Discovering Dynamics. Discovery Science 2003: 297-305 - [c55]Ljupco Todorovski, Saso Dzeroski:
Using Domain Specific Knowledge for Automated Modeling. IDA 2003: 48-59 - [c54]Saso Dzeroski, Ljupco Todorovski, Peter Ljubic:
Inductive Databases of Polynomial Equations. KDID 2003: 28-43 - [e5]Jean-François Boulicaut, Saso Dzeroski:
Proceedings of the Second International Workshop on Inductive Databases, 22 September, Cavtat-Dubrovnik, Croatia. Rudjer Boskovic Institute, Zagreb, Croatia 2003, ISBN 953-6690-34-9 [contents] - 2002
- [j20]Saso Dzeroski, Luc De Raedt:
Multi-Relational Data Mining: a Workshop Report. SIGKDD Explor. 4(2): 122-124 (2002) - [c53]Saso Dzeroski:
Relational Reinforcement Learning for Agents in Worlds with Objects. Adaptive Agents and Multi-Agents Systems 2002: 306-322 - [c52]Ljupco Todorovski, Hendrik Blockeel, Saso Dzeroski:
Ranking with Predictive Clustering Trees. ECML 2002: 444-455 - [c51]Bernard Zenko, Saso Dzeroski:
Stacking with an Extended Set of Meta-level Attributes and MLR. ECML 2002: 493-504 - [c50]Kurt Driessens, Saso Dzeroski:
Integrating Experimentation and Guidance in Relational Reinforcement Learning. ICML 2002: 115-122 - [c49]Saso Dzeroski, Bernard Zenko:
Is Combining Classifiers Better than Selecting the Best One. ICML 2002: 123-130 - [c48]Pat Langley, Javier Nicolás Sánchez, Ljupco Todorovski, Saso Dzeroski:
Inducing Process Models from Continuous Data. ICML 2002: 347-354 - [c47]Saso Dzeroski:
Learning in Rich Representations: Inductive Logic Programming and Computational Scientific Discovery. ILP 2002: 346-349 - [c46]Zdenek Zabokrtský, Petr Sgall, Saso Dzeroski:
A Machine Learning Approach to Automatic Functor Assignment in the Prague Dependency Treebank. LREC 2002 - [c45]Saso Dzeroski, Bernard Zenko:
Stacking with Multi-response Model Trees. Multiple Classifier Systems 2002: 201-211 - 2001
- [j19]Joaquim Comas, Saso Dzeroski, Karina Gibert, Ignasi R.-Roda, Miquel Sànchez-Marrè:
Knowledge discovery by means of inductive methods in wastewater treatment plannt data. AI Commun. 14(1): 45-62 (2001) - [j18]Saso Dzeroski, Luc De Raedt, Kurt Driessens:
Relational Reinforcement Learning. Mach. Learn. 43(1/2): 7-52 (2001) - [j17]Peter A. Flach, Saso Dzeroski:
Editorial: Inductive Logic Programming is Coming of Age. Mach. Learn. 44(3): 207-209 (2001) - [j16]Saso Dzeroski, Zdenek Zabokrtský:
A Machine Learning Approach to Automatic Functor Assignment in the Prague Dependency Treebank. Prague Bull. Math. Linguistics 76: 35-44 (2001) - [c44]Dimitar Hristovski, Borut Peterlin, Saso Dzeroski:
Literature-based Discovery Support System and Its Application to Disease Gene Identification. AMIA 2001 - [c43]Saso Dzeroski, Pat Langley:
Computational Discovery of Communicable Knowledge: Symposium Report. Discovery Science 2001: 45-49 - [c42]Ljupco Todorovski, Saso Dzeroski:
Theory Revision in Equation Discovery. Discovery Science 2001: 389-400 - [c41]Ljupco Todorovski, Saso Dzeroski:
Using Domain Knowledge on Population Dynamics Modeling for Equation Discovery. ECML 2001: 478-490 - [c40]Bernard Zenko, Ljupco Todorovski, Saso Dzeroski:
A Comparison of Stacking with Meta Decision Trees to Bagging, Boosting, and Stacking with other Methods. ICDM 2001: 669-670 - [c39]Dimitar Hristovski, Janez Stare, Borut Peterlin, Saso Dzeroski:
Supporting Discovery in Medicine by Association Rule Mining in Medline and UMLS. MedInfo 2001: 1344-1348 - 2000
- [j15]Dragan Gamberger, Nada Lavrac, Saso Dzeroski:
Noise Detection and Elimination in data Proprocessing: Experiments in Medical Domains. Appl. Artif. Intell. 14(2): 205-223 (2000) - [j14]Saso Dzeroski, Damjan Demsar, Jasna Grbovic:
Predicting Chemical Parameters of River Water Quality from Bioindicator Data. Appl. Intell. 13(1): 7-17 (2000) - [c38]Saso Dzeroski, Dimitar Hristovski, Borut Peterlin:
Using data mining and OLAP to discover patterns in a database of patients with Y-chromosome deletions. AMIA 2000 - [c37]Ljupco Todorovski, Saso Dzeroski, Ashwin Srinivasan, Jonathan P. Whiteley, David Gavaghan:
Discovering the Structure of Partial Differential Equations from Example Behaviour. ICML 2000: 991-998 - [c36]Saso Dzeroski, Tomaz Erjavec, Jakub Zavrel:
Morphosyntactic Tagging of Slovene: Evaluating Taggers and Tagsets. LREC 2000 - [c35]Ljupco Todorovski, Saso Dzeroski:
Combining Multiple Models with Meta Decision Trees. PKDD 2000: 54-64 - [c34]Dimitar Hristovski, Saso Dzeroski, Borut Peterlin, Anamarija Rozic-Hristovski:
Supporting Discovery in Medicine by Association Rule Mining of Bibliographic Databases. PKDD 2000: 446-451 - [e4]James Cussens, Saso Dzeroski:
Learning Language in Logic. Lecture Notes in Computer Science 1925, Springer 2000, ISBN 3-540-41145-3 [contents]
1990 – 1999
- 1999
- [j13]Saso Dzeroski, Nada Lavrac:
Editorial. Data Min. Knowl. Discov. 3(1): 5-6 (1999) - [j12]Nada Lavrac, Saso Dzeroski, Masayuki Numao:
Inductive Logic Programming for Relational Knowledge Discovery. New Gener. Comput. 17(1): 3-23 (1999) - [c33]James Cussens, Saso Dzeroski, Tomaz Erjavec:
Morphosyntactic Tagging of Slovene Using Progol. ILP 1999: 68-79 - [c32]Saso Dzeroski, Hendrik Blockeel, Boris Kompare, Stefan Kramer, Bernhard Pfahringer, Wim Van Laer:
Experiments in Predicting Biodegradability. ILP 1999: 80-91 - [c31]Saso Dzeroski, James Cussens, Suresh Manandhar:
An Introduction to Inductive Logic Programming and Learning Language in Logic. Learning Language in Logic 1999: 3-35 - [c30]Saso Dzeroski, Tomaz Erjavec:
Learning to Lemmatise Slovene Words. Learning Language in Logic 1999: 69-88 - [c29]Jure Dimec, Saso Dzeroski, Ljupco Todorovski, Dimitar Hristovski:
WWW search engine for Slovenian and English medical documents. MIE 1999: 547-552 - [c28]Hendrik Blockeel, Saso Dzeroski, Jasna Grbovic:
Simultaneous Prediction of Mulriple Chemical Parameters of River Water Quality with TILDE. PKDD 1999: 32-40 - [c27]Ljupco Todorovski, Saso Dzeroski:
Experiments in Meta-level Learning with ILP. PKDD 1999: 98-106 - [e3]Ivan Bratko, Saso Dzeroski:
Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27 - 30, 1999. Morgan Kaufmann 1999, ISBN 1-55860-612-2 [contents] - [e2]Saso Dzeroski, Peter A. Flach:
Inductive Logic Programming, 9th International Workshop, ILP-99, Bled, Slovenia, June 24-27, 1999, Proceedings. Lecture Notes in Computer Science 1634, Springer 1999, ISBN 3-540-66109-3 [contents] - 1998
- [j11]Saso Dzeroski, Steffen Schulze-Kremer, Karsten R. Heidtke, Karsten Siems, Dietrich Wettschereck, Hendrik Blockeel:
Diterpene Structure Elucidation from 13CNMR Spectra with Inductive Logic Programming. Appl. Artif. Intell. 12(5): 363-383 (1998) - [j10]Blaz Zupan, Saso Dzeroski:
Acquiring background knowledge for machine learning using function decomposition: a case study in rheumatology. Artif. Intell. Medicine 14(1-2): 101-117 (1998) - [c26]Saso Dzeroski, Nico Jacobs, Martín Molina, Carlos Moure:
ILP Experiments in Detecting Traffic Problems. ECML 1998: 61-66 - [c25]Saso Dzeroski, Luc De Raedt, Hendrik Blockeel:
Relational Reinforcement Learning. ICML 1998: 136-143 - [c24]Saso Dzeroski, Luc De Raedt, Hendrik Blockeel:
Relational Reinforcement Learning. ILP 1998: 11-22 - [c23]Suresh Manandhar, Saso Dzeroski, Tomaz Erjavec:
Learning Multilingual Morphology with CLOG. ILP 1998: 135-144 - [c22]Saso Dzeroski, Nico Jacobs, Martín Molina, Carlos Moure, Stephen H. Muggleton, Wim Van Laer:
Detecting Traffic Problems with ILP. ILP 1998: 281-290 - 1997
- [c21]Blaz Zupan, Saso Dzeroski:
Acquiring and Validating Background Knowledge for Machine Learning Using Function Decomposition. AIME 1997: 86-97 - [c20]Saso Dzeroski, George Potamias, Vassilis Moustakis, Giorgos Charissis:
Automated Revision of Expert Rules for Treating Acute Abdominal Pain in Children. AIME 1997: 98-109 - [c19]Ljupco Todorovski, Saso Dzeroski:
Declarative Bias in Equation Discovery. ICML 1997: 376-384 - [c18]Yannis Dimopoulos, Saso Dzeroski, Antonis C. Kakas:
Integrating Explanatory and Descriptive Learning in ILP. IJCAI (2) 1997: 900-907 - [c17]Saso Dzeroski, Tomaz Erjavec:
Induction of Slovene Nominal Paradigms. ILP 1997: 141-148 - [c16]Wim Van Laer, Luc De Raedt, Saso Dzeroski:
On Multi-class Problems and Discretization in Inductive Logic Programming. ISMIS 1997: 277-286 - [e1]Nada Lavrac, Saso Dzeroski:
Inductive Logic Programming, 7th International Workshop, ILP-97, Prague, Czech Republic, September 17-20, 1997, Proceedings. Lecture Notes in Computer Science 1297, Springer 1997, ISBN 3-540-63514-9 [contents] - 1996
- [j9]Nada Lavrac, Irene Weber, Darko Zupanic, Dimitar Kazakov, Olga Stepánková, Saso Dzeroski:
ILPNET Repositories on WWW: Inductive Logic Programming Systems, Datasets and Bibliography. AI Commun. 9(4): 157-206 (1996) - [j8]Nada Lavrac, Saso Dzeroski:
A Reply to Pazzani's Book Review of "Inductive Logic Programming: Techniques and Applications". Mach. Learn. 23(1): 109-111 (1996) - [c15]Dragan Gamberger, Nada Lavrac, Saso Dzeroski:
Noise Elimination in Inductive Concept Learning: A Case Study in Medical Diagnosois. ALT 1996: 199-212 - [c14]Saso Dzeroski, Steffen Schulze-Kremer, Karsten R. Heidtke, Karsten Siems, Dietrich Wettschereck:
Applying ILP to Diterpene Structure Elucidation from 13C NMR Spectra. Inductive Logic Programming Workshop 1996: 41-54 - [p1]Saso Dzeroski:
Inductive Logic Programming and Knowledge Discovery in Databases. Advances in Knowledge Discovery and Data Mining 1996: 117-152 - 1995
- [j7]Saso Dzeroski, Ljupco Todorovski:
Discovering Dynamics: From Inductive Logic Programming to Machine Discovery. J. Intell. Inf. Syst. 4(1): 89-108 (1995) - [j6]Ivan Bratko, Saso Dzeroski:
Engineering Applications of ILP. New Gener. Comput. 13(3&4): 313-333 (1995) - [c13]Saso Dzeroski, Ljupco Todorovski, Tanja Urbancic:
Handling Real Numbers in ILP: A Step Towards Better Behavioural Clones (Extended Abstract). ECML 1995: 283-286 - [c12]Saso Dzeroski:
Knowledge Discovery in a Water Quality Database. KDD 1995: 81-86 - [c11]Saso Dzeroski:
Learning First-order Clausal Theories in the Presence of Noise. SCAI 1995: 51-60 - 1994
- [b1]Nada Lavrac, Saso Dzeroski:
Inductive logic programming - techniques and applications. Ellis Horwood series in artificial intelligence, Ellis Horwood 1994, ISBN 978-0-13-457870-5, pp. I-XIX, 1-293 - [j5]Luc De Raedt, Saso Dzeroski:
First-Order jk-Clausal Theories are PAC-Learnable. Artif. Intell. 70(1-2): 375-392 (1994) - [j4]Nada Lavrac, Saso Dzeroski:
Weakening the language bias in LINUS. J. Exp. Theor. Artif. Intell. 6(1): 95-119 (1994) - [j3]Jörg-Uwe Kietz, Saso Dzeroski:
Inductive Logic Programming and Learnability. SIGART Bull. 5(1): 22-32 (1994) - [c10]Saso Dzeroski, Igor Petrovski:
Discovering Dynamics with Genetic Programming. ECML 1994: 347-350 - 1993
- [j2]Nada Lavrac, Saso Dzeroski, Vladimir Pirnat, Viljem Krizman:
The utility of background knowledge in learning medical diagnostic rules. Appl. Artif. Intell. 7(3): 273-293 (1993) - [j1]Saso Dzeroski, Nada Lavrac:
Inductive Learning in Deductive Databases. IEEE Trans. Knowl. Data Eng. 5(6): 939-949 (1993) - [c9]Saso Dzeroski, Stephen H. Muggleton, Stuart Russell:
Learnability of Constrained Logic Programs. ECML 1993: 342-347 - [c8]Saso Dzeroski, Ljupco Todorovski:
Discovering Dynamics. ICML 1993: 97-103 - [c7]Luc De Raedt, Nada Lavrac, Saso Dzeroski:
Multiple Predicate Learning. IJCAI 1993: 1037-1043 - [c6]Saso Dzeroski:
Handling Imperfetc Data in Inductive Logic Programming. SCAI 1993: 111-125 - 1992
- [c5]Nada Lavrac, Saso Dzeroski:
Background Knowledge and Declarative Bias in Inductive Concept Learning. AII 1992: 51-71 - [c4]Saso Dzeroski, Stephen H. Muggleton, Stuart Russell:
PAC-Learnability of Determinate Logic Programs. COLT 1992: 128-135 - 1991
- [c3]Nada Lavrac, Saso Dzeroski, Marko Grobelnik:
Learning Nonrecursive Definitions of Relations with LINUS. EWSL 1991: 265-281 - [c2]Saso Dzeroski, Nada Lavrac:
Learning Relations from Noisy Examples: An Empirical Comparison of LINUS and FOIL. ML 1991: 399-402 - [c1]Nada Lavrac, Saso Dzeroski, Vladimir Pirnat, Viljem Krizman:
Learning Rules for Early Diagnosis of Rheumatic Diseases. SCAI 1991: 138-149
Coauthor Index
[j122] [j120] [j117] [j113] [j111] [j108] [j107] [c164] [i23] [i22] [i20] [j101] [j100] [j98] [i18] [i16] [i15] [j95] [j93] [j92] [j90] [j89] [i11] [i10] [j86] [c150] [c149] [j83] [j82] [j81] [j78] [c147] [i5] [j75] [j74] [c144] [c142] [c141] [c140] [c139] [c138] [c137] [c136] [c135] [j70] [j67] [c133] [j63] [j60] [c122] [j57] [c119] [e10] [j54] [j50] [c116] [c112] [c111] [j47] [j44] [j40] [j39] [c101] [c100] [p8] [c97] [c96] [c93] [c87] [c77]
[j121] [i34] [j119] [j116] [j115] [j114] [d2] [i32] [j108] [j107] [c166] [i25] [j97] [i18] [i16] [j96] [j94] [i9] [j85] [c148] [i8] [i7] [c143] [c134] [e13] [e12] [i3] [j72] [c132] [j64] [j62] [e10] [c113] [j43] [j41] [j37] [c91] [p5] [p4] [e7] [c65] [c63] [c62] [c60] [j24] [c57] [c56] [c55] [c54] [c52] [c48] [c42] [c41] [c40] [c37] [c35] [c29] [c27] [c19] [j7] [c13] [c8]
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