Michael Kommenda

Publication Activity (10 Years)

Years Active: 2009-2023
Publications (10 Years): 55

Top Topics

Nonlinear Least Squares

Symbolic Regression

Top Venues

GECCO (Companion)

Publications

Philipp Fleck, Stephan M. Winkler, Michael Kommenda, Sara Silva, Leonardo Vanneschi, Michael Affenzeller
Evolutionary Algorithms for Segment Optimization in Vectorial GP. GECCO Companion (2023)
Philipp Fleck, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller
Vectorial Genetic Programming - Optimizing Segments for Feature Extraction. CoRR (2023)
Fabrício Olivetti de França, Marco Virgolin, Michael Kommenda, M. S. Majumder, Miles D. Cranmer, Guilherme Espada, Leon Ingelse, Alcides Fonseca, Mikel Landajuela, B. Petersen, Ruben Glatt, T. Nathan Mundhenk, C. S. Lee, Jacob D. Hochhalter, David L. Randall, P. Kamienny, H. Zhang, G. Dick, A. Simon, Bogdan Burlacu, Jaan Kasak, Meera Vieira Machado, Casper Wilstrup, William G. La Cava
Interpretable Symbolic Regression for Data Science: Analysis of the 2022 Competition. CoRR (2023)
Wolfgang Roland, Michael Kommenda, Gerald R. Berger-Weber
Application of Symbolic Regression in Polymer Processing. SYNASC (2022)
Gabriel Kronberger, Fabrício Olivetti de França, Bogdan Burlacu, Christian Haider, Michael Kommenda
Shape-Constrained Symbolic Regression - Improving Extrapolation with Prior Knowledge. Evol. Comput. 30 (1) (2022)
Lukas Kammerer, Gabriel Kronberger, Michael Kommenda
Symbolic Regression with Fast Function Extraction and Nonlinear Least Squares Optimization. EUROCAST (2022)
Bogdan Burlacu, Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler, Michael Affenzeller
Symbolic Regression in Materials Science: Discovering Interatomic Potentials from Data. CoRR (2022)
Bogdan Burlacu, Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler, Michael Affenzeller
Symbolic Regression in Materials Science: Discovering Interatomic Potentials from Data. GPTP (2022)
Lukas Kammerer, Gabriel Kronberger, Michael Kommenda
Symbolic Regression with Fast Function Extraction and Nonlinear Least Squares Optimization. CoRR (2022)
Gabriel Kronberger, Lukas Kammerer, Michael Kommenda
Identification of Dynamical Systems using Symbolic Regression. CoRR (2021)
William G. La Cava, Patryk Orzechowski, Bogdan Burlacu, Fabrício Olivetti de França, Marco Virgolin, Ying Jin, Michael Kommenda, Jason H. Moore
Contemporary Symbolic Regression Methods and their Relative Performance. NeurIPS Datasets and Benchmarks (2021)
Philipp Fleck, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller
Grammar-Based Vectorial Genetic Programming for Symbolic Regression. GPTP (2021)
Bogdan Burlacu, Michael Affenzeller, Michael Kommenda
On the Effectiveness of Genetic Operations in Symbolic Regression. CoRR (2021)
Philipp Fleck, Manfred Kügel, Michael Kommenda
Understanding and Preparing Data of Industrial Processes for Machine Learning Applications. CoRR (2021)
Florian Holzinger, Michael Kommenda
Preprocessing and Modeling of Radial Fan Data for Health State Prediction. CoRR (2021)
Gabriel Kronberger, Evgeniya Kabliman, Johannes Kronsteiner, Michael Kommenda
Predicting Calibration Parameter Values for Constitutive Models using Genetic Programming. CoRR (2021)
Gabriel Kronberger, Lukas Kammerer, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller
Cluster Analysis of a Symbolic Regression Search Space. CoRR (2021)
Gabriel Kronberger, Fabrício Olivetti de França, Bogdan Burlacu, Christian Haider, Michael Kommenda
Shape-constrained Symbolic Regression - Improving Extrapolation with Prior Knowledge. CoRR (2021)
William G. La Cava, Patryk Orzechowski, Bogdan Burlacu, Fabrício Olivetti de França, Marco Virgolin, Ying Jin, Michael Kommenda, Jason H. Moore
Contemporary Symbolic Regression Methods and their Relative Performance. CoRR (2021)
Michael Kommenda, Johannes Karder, Andreas Beham, Bogdan Burlacu, Gabriel Kronberger, Stefan Wagner, Michael Affenzeller
Optimization Networks for Integrated Machine Learning. CoRR (2021)
Lukas Kammerer, Gabriel Kronberger, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller
Symbolic Regression by Exhaustive Search: Reducing the Search Space Using Syntactical Constraints and Efficient Semantic Structure Deduplication. CoRR (2021)
Michael Kommenda, Andreas Beham, Michael Affenzeller, Gabriel Kronberger
Complexity Measures for Multi-objective Symbolic Regression. CoRR (2021)
Lukas Kammerer, Gabriel Kronberger, Michael Kommenda
Data Aggregation for Reducing Training Data in Symbolic Regression. CoRR (2021)
Gabriel Kronberger, Michael Kommenda, Andreas Promberger, Falk Nickel
Predicting Friction System Performance with Symbolic Regression and Genetic Programming with Factor Variables. CoRR (2021)
Michael Kommenda, Bogdan Burlacu, Gabriel Kronberger, Michael Affenzeller
Parameter identification for symbolic regression using nonlinear least squares. Genet. Program. Evolvable Mach. 21 (3) (2020)
Bogdan Burlacu, Gabriel Kronberger, Michael Kommenda
Operon C++: an efficient genetic programming framework for symbolic regression. GECCO Companion (2020)
Bogdan Burlacu, Michael Affenzeller, Gabriel Kronberger, Michael Kommenda
Online Diversity Control in Symbolic Regression via a Fast Hash-based Tree Similarity Measure. CoRR (2019)
Michael Affenzeller, Bogdan Burlacu, Viktoria Dorfer, Sebastian Dorl, Gerhard Halmerbauer, Tilman Königswieser, Michael Kommenda, Julia Vetter, Stephan M. Winkler
White Box vs. Black Box Modeling: On the Performance of Deep Learning, Random Forests, and Symbolic Regression in Solving Regression Problems. EUROCAST (1) (2019)
Bogdan Burlacu, Gabriel Kronberger, Michael Kommenda, Michael Affenzeller
Parsimony measures in multi-objective genetic programming for symbolic regression. GECCO (Companion) (2019)
Lukas Kammerer, Gabriel Kronberger, Michael Kommenda
Data Aggregation for Reducing Training Data in Symbolic Regression. EUROCAST (1) (2019)
Philipp Fleck, Manfred Kügel, Michael Kommenda
Understanding and Preparing Data of Industrial Processes for Machine Learning Applications. EUROCAST (1) (2019)
Bogdan Burlacu, Michael Affenzeller, Gabriel Kronberger, Michael Kommenda
Online Diversity Control in Symbolic Regression via a Fast Hash-based Tree Similarity Measure. CEC (2019)
Florian Holzinger, Michael Kommenda
Preprocessing and Modeling of Radial Fan Data for Health State Prediction. EUROCAST (1) (2019)
Lukas Kammerer, Gabriel Kronberger, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller
Symbolic Regression by Exhaustive Search: Reducing the Search Space Using Syntactical Constraints and Efficient Semantic Structure Deduplication. GPTP (2019)
Gabriel Kronberger, Lukas Kammerer, Michael Kommenda
Identification of Dynamical Systems Using Symbolic Regression. EUROCAST (1) (2019)
Gabriel Kronberger, Michael Kommenda, Edwin Lughofer, Susanne Saminger-Platz, Andreas Promberger, Falk Nickel, Stephan M. Winkler, Michael Affenzeller
Using robust generalized fuzzy modeling and enhanced symbolic regression to model tribological systems. Appl. Soft Comput. 69 (2018)
Gabriel Kronberger, Lukas Kammerer, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller
Cluster Analysis of a Symbolic Regression Search Space. GPTP (2018)
Philipp Fleck, Michael Kommenda, Thorsten Prante, Michael Affenzeller
Novel robustness measures for engineering design optimisation. Int. J. Simul. Process. Model. 13 (4) (2018)
Gabriel Kronberger, Michael Kommenda, Andreas Promberger, Falk Nickel
Predicting friction system performance with symbolic regression and genetic programming with factor variables. GECCO (2018)
Michael Affenzeller, Stephan M. Winkler, Bogdan Burlacu, Gabriel Kronberger, Michael Kommenda, Stefan Wagner
Dynamic observation of genotypic and phenotypic diversity for different symbolic regression GP variants. GECCO (Companion) (2017)
Michael Affenzeller, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Gabriel Kronberger, Stefan Wagner
Offspring Selection Genetic Algorithm Revisited: Improvements in Efficiency by Early Stopping Criteria in the Evaluation of Unsuccessful Individuals. EUROCAST (1) (2017)
Bogdan Burlacu, Michael Affenzeller, Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler
Schema Analysis in Tree-Based Genetic Programming. GPTP (2017)
Gabriel Kronberger, Bogdan Burlacu, Michael Kommenda, Stephan M. Winkler, Michael Affenzeller
Measures for the Evaluation and Comparison of Graphical Model Structures. EUROCAST (1) (2017)
Johannes Karder, Stefan Wagner, Andreas Beham, Michael Kommenda, Michael Affenzeller
Towards the design and implementation of optimization networks in HeuristicLab. GECCO (Companion) (2017)
Bogdan Burlacu, Michael Affenzeller, Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler
Analysis of Schema Frequencies in Genetic Programming. EUROCAST (1) (2017)
Michael Kommenda, Johannes Karder, Andreas Beham, Bogdan Burlacu, Gabriel Kronberger, Stefan Wagner, Michael Affenzeller
Optimization Networks for Integrated Machine Learning. EUROCAST (1) (2017)
Edwin Lughofer, Gabriel Kronberger, Michael Kommenda, Susanne Saminger-Platz, Andreas Promberger, Falk Nickel, Stephan M. Winkler, Michael Affenzeller
Robust Fuzzy Modeling and Symbolic Regression for Establishing Accurate and Interpretable Prediction Models in Supervising Tribological Systems. IJCCI (FCTA) (2016)
Stephan M. Winkler, Michael Affenzeller, Bogdan Burlacu, Gabriel Kronberger, Michael Kommenda, Philipp Fleck
Similarity-Based Analysis of Population Dynamics in Genetic Programming Performing Symbolic Regression. GPTP (2016)
Gabriel Kronberger, Michael Kommenda, Stephan M. Winkler, Michael Affenzeller
Using Contextual Information in Sequential Search for Grammatical Optimization Problems. EUROCAST (2015)
Bogdan Burlacu, Michael Affenzeller, Michael Kommenda
On the Effectiveness of Genetic Operations in Symbolic Regression. EUROCAST (2015)
Andreas Beham, Judith Fechter, Michael Kommenda, Stefan Wagner, Stephan M. Winkler, Michael Affenzeller
Optimization Strategies for Integrated Knapsack and Traveling Salesman Problems. EUROCAST (2015)
Michael Kommenda, Andreas Beham, Michael Affenzeller, Gabriel Kronberger
Complexity Measures for Multi-objective Symbolic Regression. EUROCAST (2015)
Andreas Scheibenpflug, Andreas Beham, Michael Kommenda, Johannes Karder, Stefan Wagner, Michael Affenzeller
Simplifying Problem Definitions in the HeuristicLab Optimization Environment. GECCO (Companion) (2015)
Stephan M. Winkler, Gabriel Kronberger, Michael Kommenda, Stefan Fink, Michael Affenzeller
Dynamics of Predictability and Variable Influences Identified in Financial Data Using Sliding Window Machine Learning. EUROCAST (2015)
Michael Kommenda, Gabriel Kronberger, Michael Affenzeller, Stephan M. Winkler, Bogdan Burlacu
Evolving Simple Symbolic Regression Models by Multi-Objective Genetic Programming. GPTP (2015)
Andreas Beham, Johannes Karder, Gabriel Kronberger, Stefan Wagner, Michael Kommenda, Andreas Scheibenpflug
Scripting and framework integration in heuristic optimization environments. GECCO (Companion) (2014)
Gerd Bramerdorfer, Stephan M. Winkler, Michael Kommenda, Günther Weidenholzer, Siegfried Silber, Gabriel Kronberger, Michael Affenzeller, Wolfgang Amrhein
Using FE Calculations and Data-Based System Identification Techniques to Model the Nonlinear Behavior of PMSMs. IEEE Trans. Ind. Electron. 61 (11) (2014)
Stephan M. Winkler, Michael Affenzeller, Gabriel Kronberger, Michael Kommenda, Bogdan Burlacu, Stefan Wagner
Sliding Window Symbolic Regression for Detecting Changes of System Dynamics. GPTP (2014)
Michael Kommenda, Michael Affenzeller, Bogdan Burlacu, Gabriel Kronberger, Stephan M. Winkler
Genetic programming with data migration for symbolic regression. GECCO (Companion) (2014)
Michael Kommenda, Gabriel Kronberger, Christoph Feilmayr, Michael Affenzeller
Data Mining using Unguided Symbolic Regression on a Blast Furnace Dataset. CoRR (2013)
Stephan M. Winkler, Michael Affenzeller, Gabriel Kronberger, Michael Kommenda, Stefan Wagner, Viktoria Dorfer, Witold Jacak, Herbert Stekel
On the use of estimated tumour marker classifications in tumour diagnosis prediction - a case study for breast cancer. Int. J. Simul. Process. Model. 8 (1) (2013)
Michael Kommenda, Michael Affenzeller, Gabriel Kronberger, Stephan M. Winkler
Nonlinear Least Squares Optimization of Constants in Symbolic Regression. EUROCAST (1) (2013)
Michael Affenzeller, Stephan M. Winkler, Gabriel Kronberger, Michael Kommenda, Bogdan Burlacu, Stefan Wagner
Gaining Deeper Insights in Symbolic Regression. GPTP (2013)
Bogdan Burlacu, Michael Affenzeller, Michael Kommenda
On the Evolutionary Behavior of Genetic Programming with Constants Optimization. EUROCAST (1) (2013)
Stefan Vonolfen, Andreas Beham, Michael Kommenda, Michael Affenzeller
Structural Synthesis of Dispatching Rules for Dynamic Dial-a-Ride Problems. EUROCAST (1) (2013)
Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler, Michael Affenzeller, Stefan Wagner
Effects of constant optimization by nonlinear least squares minimization in symbolic regression. GECCO (Companion) (2013)
Gabriel Kronberger, Michael Kommenda
Evolution of Covariance Functions for Gaussian Process Regression Using Genetic Programming. EUROCAST (1) (2013)
Gabriel Kronberger, Michael Kommenda
Evolution of Covariance Functions for Gaussian Process Regression using Genetic Programming CoRR (2013)
Bogdan Burlacu, Michael Affenzeller, Michael Kommenda, Stephan M. Winkler, Gabriel Kronberger
Visualization of genetic lineages and inheritance information in genetic programming. GECCO (Companion) (2013)
Gabriel Kronberger, Michael Kommenda, Stefan Wagner, Heinz Dobler
GPDL: a framework-independent problem definition language for grammar-guided genetic programming. GECCO (Companion) (2013)
Gabriel Kronberger, Stefan Fink, Michael Kommenda, Michael Affenzeller
Macro-Economic Time Series Modeling and Interaction Networks CoRR (2012)
Gabriel Kronberger, Stefan Wagner, Michael Kommenda, Andreas Beham, Andreas Scheibenpflug, Michael Affenzeller
Knowledge Discovery through Symbolic Regression with HeuristicLab. ECML/PKDD (2) (2012)
Michael Kommenda, Gabriel Kronberger, Stefan Wagner, Stephan M. Winkler, Michael Affenzeller
On the architecture and implementation of tree-based genetic programming in HeuristicLab. GECCO (Companion) (2012)
Gabriel Kronberger, Stefan Fink, Michael Kommenda, Michael Affenzeller
Macro-economic Time Series Modeling and Interaction Networks. EvoApplications (2) (2011)
Michael Kommenda, Gabriel Kronberger, Christoph Feilmayr, Michael Affenzeller
Data Mining Using Unguided Symbolic Regression on a Blast Furnace Dataset. EvoApplications (1) (2011)
Stephan M. Winkler, Michael Affenzeller, Gabriel Kronberger, Michael Kommenda, Stefan Wagner, Witold Jacak, Herbert Stekel
Analysis of Selected Evolutionary Algorithms in Feature Selection and Parameter Optimization for Data Based Tumor Marker Modeling. EUROCAST (1) (2011)
Gabriel Kronberger, Michael Kommenda, Michael Affenzeller
Overfitting detection and adaptive covariant parsimony pressure for symbolic regression. GECCO (Companion) (2011)
Michael Kommenda, Gabriel Kronberger, Christoph Feilmayr, Leonhard Schickmair, Michael Affenzeller, Stephan M. Winkler, Stefan Wagner
Application of Symbolic Regression on Blast Furnace and Temper Mill Datasets. EUROCAST (1) (2011)
Alexandru-Ciprian Zavoianu, Gabriel Kronberger, Michael Kommenda, Daniela Zaharie, Michael Affenzeller
Improving the Parsimony of Regression Models for an Enhanced Genetic Programming Process. EUROCAST (1) (2011)
Christian Frech, Michael Kommenda, Viktoria Dorfer, Thomas Kern, Helmut Hintner, Johann W. Bauer, Kamil Önder
Improved homology-driven computational validation of protein-protein interactions motivated by the evolutionary gene duplication and divergence hypothesis. BMC Bioinform. 10 (2009)