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Ljupco Todorovski
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2020 – today
- 2024
- [j26]Nina Omejc
, Bostjan Gec, Jure Brence
Probabilistic grammars for modeling dynamical systems from coarse, noisy, and partial data. Mach. Learn. 113(10): 7689-7721 (2024) - [i14]Sebastian Meznar, Saso Dzeroski, Ljupco Todorovski:
Quantifying Behavioural Distance Between Mathematical Expressions. CoRR abs/2408.11515 (2024) - 2023
- [j25]Jure Brence
Dimensionally-consistent equation discovery through probabilistic attribute grammars. Inf. Sci. 632: 742-756 (2023) - [j24]Sebastian Meznar
Efficient generator of mathematical expressions for symbolic regression. Mach. Learn. 112(11): 4563-4596 (2023) - [j23]Sebastian Meznar, Saso Dzeroski, Ljupco Todorovski:
Correction to: efficient generator of mathematical expressions for symbolic regression. Mach. Learn. 112(12): 5191 (2023) - [j22]Jure Brence
Boosting the performance of quantum annealers using machine learning. Quantum Mach. Intell. 5(1): 1-11 (2023) - [c44]Andrej Bauer, Matej Petkovic, Ljupco Todorovski:
MLFMF: Data Sets for Machine Learning for Mathematical Formalization. NeurIPS 2023 - [d1]Nina Omejc
Dynobench - extended Strogatz benchmark for system identification methods. Zenodo, 2023 - [i13]Sebastian Meznar, Saso Dzeroski, Ljupco Todorovski:
Efficient Generator of Mathematical Expressions for Symbolic Regression. CoRR abs/2302.09893 (2023) - [i12]Andrej Bauer, Matej Petkovic, Ljupco Todorovski:
MLFMF: Data Sets for Machine Learning for Mathematical Formalization. CoRR abs/2310.16005 (2023) - 2022
- [j21]Jasmin Bogatinovski
Comprehensive comparative study of multi-label classification methods. Expert Syst. Appl. 203: 117215 (2022) - [j20]Dejan Ravselj
A Review of Digital Era Governance Research in the First Two Decades: A Bibliometric Study. Future Internet 14(5): 126 (2022) - [j19]Jasmin Bogatinovski, Ljupco Todorovski, Saso Dzeroski
Explaining the performance of multilabel classification methods with data set properties. Int. J. Intell. Syst. 37(9): 6080-6122 (2022) - [c43]Bostjan Gec
Discovery of Differential Equations Using Probabilistic Grammars. DS 2022: 22-31 - [i11]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) - [i10]Urh Primozic, Ljupco Todorovski, Matej Petkovic:
P(Expression|Grammar): Probability of deriving an algebraic expression with a probabilistic context-free grammar. CoRR abs/2212.00751 (2022) - 2021
- [j18]Jure Brence
Probabilistic grammars for equation discovery. Knowl. Based Syst. 224: 107077 (2021) - [c42]Dino Aljevic, Ljupco Todorovski, Sanda Martincic-Ipsic:
Extractive Text Summarization Based on Selectivity Ranking. INISTA 2021: 1-6 - [i9]Jasmin Bogatinovski, Ljupco Todorovski, Saso Dzeroski, Dragi Kocev:
Comprehensive Comparative Study of Multi-Label Classification Methods. CoRR abs/2102.07113 (2021) - [i8]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) - [i7]Rakib Hassan Pran
Predicting Hidden Links and Missing Nodes in Scale-Free Networks with Artificial Neural Networks. CoRR abs/2109.12331 (2021) - 2020
- [j17]Nikola Simidjievski
Equation Discovery for Nonlinear System Identification. IEEE Access 8: 29930-29943 (2020) - [j16]Jovan Tanevski
Combinatorial search for selecting the structure of models of dynamical systems with equation discovery. Eng. Appl. Artif. Intell. 89: 103423 (2020) - [c41]Zan Ternik
Assessing the Agreement in the Bebras Tasks Categorisation. ISSEP 2020: 30-41 - [i6]Jure Brence, Ljupco Todorovski, Saso Dzeroski:
Probabilistic Grammars for Equation Discovery. CoRR abs/2012.00428 (2020)
2010 – 2019
- 2019
- [j15]Ziga Luksic
Meta-Model Framework for Surrogate-Based Parameter Estimation in Dynamical Systems. IEEE Access 7: 181829-181841 (2019) - [c40]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 - [i5]Marc G. Leguia, Zoran Levnajic, Ljupco Todorovski, Bernard Zenko:
Reconstructing dynamical networks via feature ranking. CoRR abs/1902.03896 (2019) - [i4]Ziga Luksic, Jovan Tanevski, Saso Dzeroski, Ljupco Todorovski:
Meta-Model Framework for Surrogate-Based Parameter Estimation in Dynamical Systems. CoRR abs/1906.09088 (2019) - [i3]Nikola Simidjievski, Ljupco Todorovski, Jus Kocijan, Saso Dzeroski:
Equation Discovery for Nonlinear System Identification. CoRR abs/1907.00821 (2019) - 2017
- [c39]Ziga Luksic, Jovan Tanevski
General Meta-Model Framework for Surrogate-Based Numerical Optimization. DS 2017: 51-66 - [c38]Jovan Tanevski
Process-Based Modeling and Design of Dynamical Systems. ECML/PKDD (3) 2017: 378-382 - [e7]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] - [e6]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] - [r4]Ljupco Todorovski:
Equation Discovery. Encyclopedia of Machine Learning and Data Mining 2017: 410-414 - [r3]Ljupco Todorovski:
Inductive Process Modeling. Encyclopedia of Machine Learning and Data Mining 2017: 656-658 - [i2]Sanda Martincic-Ipsic, Tanja Milicic, Ljupco Todorovski:
The Influence of Feature Representation of Text on the Performance of Document Classification. CoRR abs/1707.01321 (2017) - [i1]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
- [j14]Jovan Tanevski
Learning stochastic process-based models of dynamical systems from knowledge and data. BMC Syst. Biol. 10: 30 (2016) - [c37]Nikola Simidjievski
Learning Ensembles of Process-Based Models by Bagging of Random Library Samples. DS 2016: 245-260 - 2015
- [j13]Jovan Tanevski
Domain-specific model selection for structural identification of the Rab5-Rab7 dynamics in endocytosis. BMC Syst. Biol. 9: 31 (2015) - [j12]Nikola Simidjievski
Predicting long-term population dynamics with bagging and boosting of process-based models. Expert Syst. Appl. 42(22): 8484-8496 (2015) - [j11]Nusa Erman, Ljupco Todorovski:
The effects of measurement error in case of scientific network analysis. Scientometrics 104(2): 453-473 (2015) - 2014
- [e5]Saso Dzeroski
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
- [c36]Jovan Tanevski
Inductive Process Modeling of Rab5-Rab7 Conversion in Endocytosis. Discovery Science 2013: 265-280 - 2012
- [c35]Ljupco Todorovski, Will Bridewell, Pat Langley:
Discovering Constraints for Inductive Process Modeling. AAAI 2012: 256-262 - 2011
- [j10]Katerina Tashkova
Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis. BMC Syst. Biol. 5: 159 (2011) - [j9]Natasa Atanasova, Saso Dzeroski
Automated discovery of a model for dinoflagellate dynamics. Environ. Model. Softw. 26(5): 658-668 (2011) - 2010
- [c34]Will Bridewell, Ljupco Todorovski:
The Induction and Transfer of Declarative Bias. AAAI 2010: 401-406 - [c33]Nusa Erman, Ljupco Todorovski:
Analyzing the Structure of the EGOV Conference Community. EGOV 2010: 73-84 - [r2]Ljupco Todorovski:
Equation Discovery. Encyclopedia of Machine Learning 2010: 327-330 - [r1]Ljupco Todorovski:
Inductive Process Modeling. Encyclopedia of Machine Learning 2010: 537
2000 – 2009
- 2009
- [c32]Nusa Erman, Ljupco Todorovski:
Mapping the E-Government Research with Social Network Analysis. EGOV 2009: 13-25 - 2008
- [j8]Will Bridewell, Pat Langley, Ljupco Todorovski, Saso Dzeroski
Inductive process modeling. Mach. Learn. 71(1): 1-32 (2008) - [c31]Aleksandar Peckov, Saso Dzeroski
A Minimal Description Length Scheme for Polynomial Regression. PAKDD 2008: 284-295 - 2007
- [c30]Ljupco Todorovski, Mateja Kunstelj, Mirko Vintar:
Reference Models for E-Services Integration Based on Life-Events. EGOV 2007: 92-103 - [c29]Will Bridewell, Ljupco Todorovski:
Learning Declarative Bias. ILP 2007: 63-77 - [c28]Will Bridewell, Stuart R. Borrett
Extracting constraints for process modeling. K-CAP 2007: 87-94 - [p2]Saso Dzeroski
Computational Discovery of Scientific Knowledge. Computational Discovery of Scientific Knowledge 2007: 1-14 - [p1]Ljupco Todorovski, Saso Dzeroski
Integrating Domain Knowledge in Equation Discovery. Computational Discovery of Scientific Knowledge 2007: 69-97 - [e4]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] - 2006
- [j7]Pat Langley, Oren Shiran, Jeff Shrager, Ljupco Todorovski, Andrew Pohorille:
Constructing explanatory process models from biological data and knowledge. Artif. Intell. Medicine 37(3): 191-201 (2006) - [e3]Ljupco Todorovski, Nada Lavrac, Klaus P. Jantke:
Discovery Science, 9th International Conference, DS 2006, Barcelona, Spain, October 7-10, 2006, Proceedings. Lecture Notes in Computer Science 4265, Springer 2006, ISBN 3-540-46491-3 [contents] - 2005
- [c27]Ljupco Todorovski, Will Bridewell, Oren Shiran, Pat Langley:
Inducing Hierarchical Process Models in Dynamic Domains. AAAI 2005: 892-897 - [c26]Will Bridewell, Narges Bani Asadi, Pat Langley, Ljupco Todorovski:
Reducing overfitting in process model induction. ICML 2005: 81-88 - 2004
- [j6]Nada Lavrac, Branko Kavsek, Peter A. Flach, Ljupco Todorovski:
Subgroup Discovery with CN2-SD. J. Mach. Learn. Res. 5: 153-188 (2004) - [c25]Saso Dzeroski
Inductive Queries on Polynomial Equations. Constraint-Based Mining and Inductive Databases 2004: 127-154 - [c24]Saso Dzeroski
Inductive Databases of Polynomial Equations. DaWaK 2004: 159-168 - [c23]Ljupco Todorovski, Peter Ljubic, Saso Dzeroski
Inducing Polynomial Equations for Regression. ECML 2004: 441-452 - [c22]Ljupco Todorovski, Saso Dzeroski:
Integrating Knowledge-Driven and Data-Driven Approaches to Modeling. EnviroInfo (1) 2004: 215-226 - [c21]Branko Kavsek, Nada Lavrac, Ljupco Todorovski:
ROC Analysis of Example Weighting in Subgroup Discovery. ROCAI 2004: 55-60 - 2003
- [j5]Ljupco Todorovski, Saso Dzeroski
Combining Classifiers with Meta Decision Trees. Mach. Learn. 50(3): 223-249 (2003) - [c20]Saso Dzeroski
Modelling Soil Radon Concentration for Earthquake Prediction. Discovery Science 2003: 87-99 - [c19]Saso Dzeroski
Using Constraints in Discovering Dynamics. Discovery Science 2003: 297-305 - [c18]Ljupco Todorovski, Saso Dzeroski
Using Domain Specific Knowledge for Automated Modeling. IDA 2003: 48-59 - [c17]Saso Dzeroski, Ljupco Todorovski, Peter Ljubic:
Inductive Databases of Polynomial Equations. KDID 2003: 28-43 - [e2]Nada Lavrac, Dragan Gamberger, Ljupco Todorovski, Hendrik Blockeel:
Machine Learning: ECML 2003, 14th European Conference on Machine Learning, Cavtat-Dubrovnik, Croatia, September 22-26, 2003, Proceedings. Lecture Notes in Computer Science 2837, Springer 2003, ISBN 3-540-20121-1 [contents] - [e1]Nada Lavrac, Dragan Gamberger, Hendrik Blockeel, Ljupco Todorovski:
Knowledge Discovery in Databases: PKDD 2003, 7th European Conference on Principles and Practice of Knowledge Discovery in Databases, Cavtat-Dubrovnik, Croatia, September 22-26, 2003, Proceedings. Lecture Notes in Computer Science 2838, Springer 2003, ISBN 3-540-20085-1 [contents] - 2002
- [c16]Ljupco Todorovski, Hendrik Blockeel
Ranking with Predictive Clustering Trees. ECML 2002: 444-455 - [c15]Nada Lavrac, Peter A. Flach, Branko Kavsek, Ljupco Todorovski:
Adapting classification rule induction to subgroup discovery. ICDM 2002: 266-273 - [c14]Pat Langley, Javier Nicolás Sánchez, Ljupco Todorovski, Saso Dzeroski:
Inducing Process Models from Continuous Data. ICML 2002: 347-354 - 2001
- [j4]Samo Ribaric, Ljupco Todorovski, Jure Dimec, Tomaz Lunder:
Presentation of dermatological images on the Internet. Comput. Methods Programs Biomed. 65(2): 111-121 (2001) - [c13]Ljupco Todorovski, Saso Dzeroski
Theory Revision in Equation Discovery. Discovery Science 2001: 389-400 - [c12]Ljupco Todorovski, Saso Dzeroski
Using Domain Knowledge on Population Dynamics Modeling for Equation Discovery. ECML 2001: 478-490 - [c11]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 - 2000
- [j3]Irena Nancovska, Anton Jeglic, Dusan Fefer, Ljupco Todorovski:
Deterministic predictive models for DC voltage reference source control. IEEE Trans. Ind. Electron. 47(1): 186-192 (2000) - [c10]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 - [c9]Ljupco Todorovski, Saso Dzeroski
Combining Multiple Models with Meta Decision Trees. PKDD 2000: 54-64 - [c8]Ljupco Todorovski, Peter A. Flach, Nada Lavrac:
Predictive Performance of Weghted Relative Accuracy. PKDD 2000: 255-264
1990 – 1999
- 1999
- [j2]Irena Nancovska, Anton Jeglic, Dusan Fefer, Ljupco Todorovski:
Equation Discovery System And Neural Networks For Short-Term Dc Voltage Prediction. Informatica (Slovenia) 23(4) (1999) - [c7]Jure Dimec, Saso Dzeroski
WWW search engine for Slovenian and English medical documents. MIE 1999: 547-552 - [c6]Eva Klemencic, Ljupco Todorovski:
Analysis of free MEDLINE on the WWW. MIE 1999: 553-556 - [c5]Ljupco Todorovski, Samo Ribaric, Jure Dimec, Emil Hudomalj, Tomaz Lunder:
Organization and dissemination of multimedia medical databases on the WWW. MIE 1999: 557-561 - [c4]Ljupco Todorovski, Saso Dzeroski
Experiments in Meta-level Learning with ILP. PKDD 1999: 98-106 - 1997
- [c3]Ljupco Todorovski, Saso Dzeroski:
Declarative Bias in Equation Discovery. ICML 1997: 376-384 - 1995
- [j1]Saso Dzeroski
Discovering Dynamics: From Inductive Logic Programming to Machine Discovery. J. Intell. Inf. Syst. 4(1): 89-108 (1995) - [c2]Saso Dzeroski
Handling Real Numbers in ILP: A Step Towards Better Behavioural Clones (Extended Abstract). ECML 1995: 283-286 - 1993
- [c1]Saso Dzeroski, Ljupco Todorovski:
Discovering Dynamics. ICML 1993: 97-103
Coauthor Index
[j26] [i14] [j25] [j24] [j23] [j22] [d1] [i13] [j21] [j19] [c43] [i11] [j18] [i9] [i8] [j17] [j16] [i6] [j15] [c40] [i4] [i3] [c39] [c38] [e7] [e6] [i1] [j14] [c37] [j13] [j12] [e5] [c36] [j10] [j9] [j8] [c31] [p2] [p1] [e4] [c25] [c24] [c23] [c22] [j5] [c20] [c19] [c18] [c17] [c16] [c14] [c13] [c12] [c11] [c10] [c9] [c7] [c4] [c3] [j1] [c2] [c1]
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last updated on 2024-11-07 20:34 CET by the dblp team
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