L. Todorovski

发表

Evolutionary Computing

Subbarao Kambhampati, Krzysztof Krawiec, Moshe Sipper, 1997, Lecture Notes in Computer Science.

Knowledge Discovery in Databases: PKDD 2003

Hendrik Blockeel, Dragan Gamberger, Nada Lavrač, 2003, Lecture Notes in Computer Science.

Evaluating Context Features for Medical Relation Mining

Paul Buitelaar, Daniel Sonntag, Špela Vintar, 2003 .

Combinatorial search for selecting the structure of models of dynamical systems with equation discovery

Saso Dzeroski, Jovan Tanevski, Ljupco Todorovski, 2020, Eng. Appl. Artif. Intell..

The influence of parameter fitting methods on model structure selection in automated modeling of aquatic ecosystems

Sašo Džeroski, Nataša Atanasova, Ljupčo Todorovski, 2012 .

Radon in soil gas: How to identify anomalies caused by earthquakes

Sašo Džeroski, Ljupčo Todorovski, B. Zmazek, 2005 .

Application of decision trees to the analysis of soil radon data for earthquake prediction.

L Todorovski, S. Džeroski, L. Todorovski, 2003, Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine.

Modeling and prediction of phytoplankton growth with equation discovery: case study — Lake Glumsø, Denmark

Sašo Džeroski, Boris Kompare, Ljupčo Todorovski, 2001 .

Multitarget Polynomial Regression with Constraints

S. Džeroski, L. Todorovski, Aleksandar Peckov, 2007 .

Late somatic sequelae after treatment of childhood cancer in Slovenia

L. Todorovski, B. Jereb, N. Erman, 2012, BMC Research Notes.

SUMO-Supermodeling by combining imperfect models

L. Todorovski, N. Simidjievski, Darko Cerepnalkoski, 2012 .

SUMO-Supermodeling by combining imperfect models Year 2 Report-Workpackage 7

P. Panov, L. Todorovski, J. Tanevski, 2012 .

Inductive process modeling

Saso Dzeroski, Pat Langley, Ljupco Todorovski, 2008, Machine Learning.

Learning bagged models of dynamic systems

S. Džeroski, L. Todorovski, N. Simidjievski, 2013 .

Equation Discovery

Ljupco Todorovski, L. Todorovski, 2017, Encyclopedia of Machine Learning and Data Mining.

Discovering the Structure of Partial Differential Equations from Example Behaviour

Ashwin Srinivasan, David Gavaghan, Saso Dzeroski, 2000, ICML.

Inducing Process Models from Continuous Data

Saso Dzeroski, Pat Langley, Ljupco Todorovski, 2002, ICML.

Explanation

Subbarao Kambhampati, Krzysztof Krawiec, Moshe Sipper, 1953, Cladistics : the international journal of the Willi Hennig Society.

Inverse Resolution

Pierre Flener, Eamonn J. Keogh, Ricardo Vilalta, 2010, Encyclopedia of Machine Learning and Data Mining.

Computational Discovery of Scientific Knowledge

Saso Dzeroski, Pat Langley, Ljupco Todorovski, 2007, Computational Discovery of Scientific Knowledge.

Inducing Process-Based Models of Dynamic Systems from Multiple Data Sets

S. Džeroski, L. Todorovski, Katerina Taskova, 2008 .

The Network-Untangling Problem: From Interactions to Activity Timelines

S. Džeroski, L. Todorovski, C. Vens, 2017 .

Application of machine learning methods to palaeoecological data

S. Džeroski, L. Todorovski, M. Debeljak, 2006 .

P(Expression|Grammar): Probability of deriving an algebraic expression with a probabilistic context-free grammar

L. Todorovski, Matej Petković, U. Primozic, 2022, 2212.00751.

Discovery Science

Sašo Džeroski, Ljupco Todorovski, Dragi Kocev, 2014, Lecture Notes in Computer Science.

Predicting long-term population dynamics with bagging and boosting of process-based models

Nikola Simidjievski, Sašo Džeroski, Ljupčo Todorovski, 2015, Expert Syst. Appl..

A comparison of stacking with meta decision trees to other combining methods

Ljupčo Todorovski, Bernard Ženko, L. Todorovski, 2001 .

Explaining the performance of multilabel classification methods with data set properties pdf

Saso Dzeroski, Ljupco Todorovski, Dragi Kocev, 2021, Int. J. Intell. Syst..

Relational ranking with predictive clustering trees

Saso Dzeroski, Hendrik Blockeel, Ljupčo Todorovski, 2002 .

A comparison of stacking with meta decision trees to bagging, boosting, and stacking with other methods

Bernard Zenko, Saso Dzeroski, Ljupco Todorovski, 2001, Proceedings 2001 IEEE International Conference on Data Mining.

A comparison of stacking with MDTs to bagging, boosting, and other stacking methods

Ljupčo Todorovski, Bernard Ženko, L. Todorovski, 2001 .

Evaluation Data

Joshua D. Knowles, S. Kambhampati, T. Heskes, 2010, Encyclopedia of Machine Learning.

Hypogonadism After Childhood Cancer Treatment

L. Todorovski, L. Zaletel, B. Jereb, 2012 .

Integrating Domain Knowledge in Equation Discovery

Saso Dzeroski, Ljupco Todorovski, S. Džeroski, 2007, Computational Discovery of Scientific Knowledge.

Using equation discovery to revise an Earth ecosystem model of the carbon net production

Pat Langley, Sašo Džeroski, Ljupčo Todorovski, 2003 .

Subgroup Discovery with CN2-SD

Peter A. Flach, Branko Kavsek, Nada Lavrac, 2004, J. Mach. Learn. Res..

Report on the Experiments with Feature Selection in Meta-Level Learning

Carlos Soares, Pavel Brazdil, Ljupco Todorovski, 2000 .

The Influence of Feature Representation of Text on the Performance of Document Classification pdf

Ljupco Todorovski, Sanda Martincic-Ipsic, Tanja Milicic, 2017, Applied Sciences.

Evolutionary Computing

Thomas E. Potok, Joshua D. Knowles, Robert M. Patton, 2019, Encyclopedia of Machine Learning and Data Mining.

Application of automated model discovery from data and expert knowledge to a real-world domain: Lake Glumsø

Sašo Džeroski, Boris Kompare, Nataša Atanasova, 2008 .

Comprehensive Comparative Study of Multi-Label Classification Methods pdf

Saso Dzeroski, Ljupco Todorovski, Dragi Kocev, 2021, Expert Syst. Appl..

A Review of Digital Era Governance Research in the First Two Decades: A Bibliometric Study

L. Todorovski, Aleksander Aristovnik, Dejan Ravšelj, 2022, Future Internet.

Decoupling approximation robustly reconstructs directed dynamical networks pdf

Zoran Levnajic, Bernard Zenko, Saso Dzeroski, 2017, New Journal of Physics.

Reference Models for E-Services Integration Based on Life-Events

Ljupco Todorovski, Mateja Kunstelj, Mirko Vintar, 2007, EGOV.

Participatory policy process design: lessons learned from three European regions

Francesco Molinari, Mateja Kunstelj, Ljupčo Todorovski, 2011 .

Radon in a thermal spring: identification of anomalies related to seismic activity.

S. Džeroski, L. Todorovski, J. Vaupotic, 2006, Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine.

Radon anomalies in soil gas caused by seismic activity

Sašo Džeroski, Ljupčo Todorovski, Mladen Živčić, 2004 .

Modelling Soil Radon Concentration for Earthquake Prediction

Saso Dzeroski, Ljupco Todorovski, Ivan Kobal, 2003, Discovery Science.

Probabilistic Grammars for Equation Discovery pdf

Saso Dzeroski, Ljupco Todorovski, Jure Brence, 2020, Knowl. Based Syst..

Combining Classifiers with Meta Decision Trees

Saso Dzeroski, Ljupco Todorovski, S. Džeroski, 2003, Machine Learning.

Adapting classification rule induction to subgroup discovery

Peter A. Flach, Branko Kavsek, Nada Lavrac, 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..

Repetitive interpolation: A robust algorithm for DTM generation from Aerial Laser Scanner Data in forested terrain☆

Norbert Pfeifer, Sašo Džeroski, Krištof Oštir, 2007 .

Equation discovery for systems biology: finding the structure and dynamics of biological networks from time course data.

Ljupco Todorovski, Saso Dzeroski, S. Džeroski, 2008, Current opinion in biotechnology.

Inducing Polynomial Equations for Regression

Saso Dzeroski, Ljupco Todorovski, Peter Ljubic, 2004, ECML.

Support for Information Seeking on the Medical Library Web

Dimitar Hristovski, Anamarija Rozic-Hristovski, Ljupčo Todorovski, 1999 .

Declarative Bias in Equation Discovery

Saso Dzeroski, Ljupco Todorovski, S. Džeroski, 1997, ICML.

Automated discovery of a model for dinoflagellate dynamics

Saso Dzeroski, Ljupco Todorovski, Boris Kompare, 2011, Environ. Model. Softw..

Modeling the Dynamics of Biological Networks from Time Course Data

Sašo Džeroski, Ljupčo Todorovski, S. Džeroski, 2010 .

Modelling the outcrossing between genetically modified and conventional maize with equation discovery

Sašo Džeroski, Aneta Ivanovska, Marko Debeljak, 2009 .

Constructing a library of domain knowledge for automated modelling of aquatic ecosystems

Sašo Džeroski, Boris Kompare, Nataša Atanasova, 2006 .

Automated modelling of a food web in lake Bled using measured data and a library of domain knowledge

Friedrich Recknagel, Sašo Džeroski, Boris Kompare, 2006 .

Computational Assemblage of Ordinary Differential Equations for Chlorophyll-a Using a Lake Process Equation Library and Measured Data of Lake Kasumigaura

Friedrich Recknagel, Sašo Džeroski, Boris Kompare, 2006 .

Integrating Knowledge-Driven and Data-Driven Approaches to Modeling

Saso Dzeroski, Ljupco Todorovski, S. Džeroski, 2006, EnviroInfo.

Inductive Queries on Polynomial Equations

Saso Dzeroski, Ljupco Todorovski, Peter Ljubic, 2004, Constraint-Based Mining and Inductive Databases.

Learning population dynamics models from data and domain knowledge

Sašo Džeroski, Ljupčo Todorovski, S. Džeroski, 2003 .

Using Constraints in Discovering Dynamics

Saso Dzeroski, Ljupco Todorovski, Peter Ljubic, 2003, Discovery Science.

Using Domain Specific Knowledge for Automated Modeling

Saso Dzeroski, Ljupco Todorovski, S. Džeroski, 2003, IDA.

Encoding and Using Domain Knowledge on Population Dynamics for Equation Discovery

Sašo Džeroski, Ljupčo Todorovski, S. Džeroski, 2002 .

Theory Revision in Equation Discovery

Saso Dzeroski, Ljupco Todorovski, S. Džeroski, 2001, Discovery Science.

Using Domain Knowledge on Population Dynamics Modeling for Equation Discovery

Saso Dzeroski, Ljupco Todorovski, S. Džeroski, 2001, ECML.

Deterministic predictive models for DC voltage reference source control

Ljupco Todorovski, Dusan Fefer, Anton Jeglic, 2000, IEEE Trans. Ind. Electron..

Equation discovery with ecological applications

Ivan Bratko, Sašo Džeroski, Boris Kompare, 1999 .

Boosting the performance of quantum annealers using machine learning

S. Džeroski, D. Mihailovic, L. Todorovski, 2022, Quantum Machine Intelligence.

Proper versus Ad-Hoc MDL Principle for Polynomial Regression

S. Džeroski, L. Todorovski, Aleksandar Peckov, 2006 .

Reinforcement learning approach for train rescheduling on a single-track railway

Marijan Žura, Rok Marsetič, Darja Šemrov, 2016 .

Equation Discovery

Ljupco Todorovski, L. Todorovski, 2010, Encyclopedia of Machine Learning and Data Mining.

Computational Discovery of Scientific Knowledge, Introduction, Techniques, and Applications in Environmental and Life Sciences

Sašo Džeroski, Ljupčo Todorovski, S. Džeroski, 2007, Computational Discovery of Scientific Knowledge.

Dimensionally-consistent equation discovery through probabilistic attribute grammars

S. Džeroski, L. Todorovski, Jure Brence, 2023, Inf. Sci..

Efficient Generator of Mathematical Expressions for Symbolic Regression

S. Džeroski, L. Todorovski, Sebastian Mežnar, 2023, ArXiv.

Equation Discovery for Nonlinear System Identification

Saso Dzeroski, Nikola Simidjievski, Ljupco Todorovski, 2019, IEEE Access.

Towards reusable process-based models of dynamical systems: A case study in the domain of aquatic ecosystems

Saso Dzeroski, Nikola Simidjievski, Pance Panov, 2019, 2019 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO).

Process-Based Modeling and Design of Dynamical Systems

Saso Dzeroski, Nikola Simidjievski, Jovan Tanevski, 2017, ECML/PKDD.

Learning Ensembles of Process-Based Models by Bagging of Random Library Samples

Saso Dzeroski, Nikola Simidjievski, Ljupco Todorovski, 2016, DS.

Process-based design of dynamical biological systems

Sašo Džeroski, Jovan Tanevski, Ljupčo Todorovski, 2016, Scientific Reports.

Modeling Dynamic Systems with Efficient Ensembles of Process-Based Models

Nikola Simidjievski, Sašo Džeroski, Ljupčo Todorovski, 2016, PloS one.

Learning stochastic process-based models of dynamical systems from knowledge and data

Saso Dzeroski, Jovan Tanevski, Ljupco Todorovski, 2016, BMC Systems Biology.

Domain-specific model selection for structural identification of the Rab5-Rab7 dynamics in endocytosis

Saso Dzeroski, Jovan Tanevski, Ljupco Todorovski, 2015, BMC Systems Biology.

Learning ensembles of population dynamics models and their application to modelling aquatic ecosystems

Nikola Simidjievski, Sašo Džeroski, Ljupčo Todorovski, 2015 .

Inductive Process Modeling of Rab5-Rab7 Conversion in Endocytosis

Saso Dzeroski, Jovan Tanevski, Ljupco Todorovski, 2013, Discovery Science.

Discovering Constraints for Inductive Process Modeling

Pat Langley, Ljupco Todorovski, Will Bridewell, 2012, AAAI.

The Induction and Transfer of Declarative Bias

Ljupco Todorovski, Will Bridewell, Will Bridewell, 2010, AAAI.

Cross-Domain Transfer of Constraints for Inductive ProcessModeling

Will Bridewell, L. Todorovski, 2008 .

Using domain knowledge for automated modelling of dynamic systems with equation discovery

Ljupčo Todorovski, L. Todorovski, 2003 .

Discovering Dynamics

Saso Dzeroski, Ljupco Todorovski, S. Džeroski, 1993, ICML.

Automated modelling of urban runoff based on domain knowledge and equation discovery

S. Džeroski, L. Todorovski, N. Atanasova, 2021, Journal of Hydrology.

Modelling and prediction of phytoplankton growth with equation discovery

Sašo Džeroski, Boris Kompare, Ljupčo Todorovski, 1998 .

Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis

Saso Dzeroski, Ljupco Todorovski, Jurij Silc, 2011, BMC Systems Biology.

Reconstructing dynamical networks via feature ranking

Zoran Levnajic, Bernard Zenko, Ljupco Todorovski, 2019, Chaos.

The effects of measurement error in case of scientific network analysis

L. Todorovski, N. Erman, Nuša Erman, 2015, Scientometrics.

Mapping the E-Government Research with Social Network Analysis

Ljupco Todorovski, Nusa Erman, L. Todorovski, 2009, EGOV.

Extensive evaluation of the generalized relevance network approach to inferring gene regulatory networks

Sašo Džeroski, Ljupčo Todorovski, Vladimir Kuzmanovski, 2018, GigaScience.

Inductive Databases of Polynomial Equations

Saso Dzeroski, Ljupco Todorovski, Peter Ljubic, 2004, KDID.

Machine Learning: ECML 2003

Hendrik Blockeel, Dragan Gamberger, Nada Lavrač, 2003, Lecture Notes in Computer Science.

Meta-Model Framework for Surrogate-Based Parameter Estimation in Dynamical Systems

Saso Dzeroski, Jovan Tanevski, Ljupco Todorovski, 2019, IEEE Access.

Ranking with Predictive Clustering Trees

Saso Dzeroski, Hendrik Blockeel, Ljupco Todorovski, 2002, ECML.

General Meta-Model Framework for Surrogate-Based Numerical Optimization

Saso Dzeroski, Jovan Tanevski, Ljupco Todorovski, 2017, DS.

Integrating knowledge-based and data-driven modeling of population dynamics

Sašo Džeroski, Ljupčo Todorovski, S. Džeroski, 2001 .

Late somatic sequelae after treatment of childhood cancer in Slovenia

L. Todorovski, B. Jereb, Nuša Erman, 2012, BMC Research Notes.

Classification tree analysis of second neoplasms in survivors of childhood cancer

L. Todorovski, J. Jazbec, B. Jereb, 2007, BMC Cancer.

Explanation

Shiau Hong Lim, S. Kambhampati, T. Heskes, 1953, Cladistics : the international journal of the Willi Hennig Society.

Efficient Generator of Mathematical Expressions for Symbolic Regression

S. Džeroski, L. Todorovski, Sebastian Mežnar, 2023, Machine-mediated learning.

Extracting constraints for process modeling

Ljupco Todorovski, Will Bridewell, Stuart R. Borrett, 2007, K-CAP '07.

Rule induction for subgroup discovery with CN2-SD

Peter A. Flach, Nada Lavrač, L Todorovski, 2002 .

Users' information-seeking behavior on a medical library Website.

Dimitar Hristovski, Ljupco Todorovski, Anamarija Rozic-Hristovsk, 2002, Journal of the Medical Library Association : JMLA.

Handling Real Numbers in ILP: A Step Towards Better Behavioural Clones (Extended Abstract)

Saso Dzeroski, Ljupco Todorovski, Tanja Urbancic, 1995, ECML.

Discovering dynamics: From inductive logic programming to machine discovery

Saso Dzeroski, Ljupco Todorovski, S. Džeroski, 1993, Journal of Intelligent Information Systems.

Predictive Performance of Weghted Relative Accuracy

Peter A. Flach, Nada Lavrac, Ljupco Todorovski, 2000, PKDD.

Combining Classifiers with Meta Decision Trees

S. Džeroski, L. Todorovski, 2003, Machine Learning.

Machine Learning and Knowledge Discovery in Databases

Donato Malerba, Dimitrios Gunopulos, Thomas Hofmann, 2017, Lecture Notes in Computer Science.

Probabilistic grammars for modeling dynamical systems from coarse, noisy, and partial data

S. Džeroski, L. Todorovski, Ljupÿco Todorovski, 2024, Machine Learning.