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2020 – today
- 2024
- [j12]Florian Bachinger, Lisa Ehrlinger, Gabriel Kronberger, Wolfram Wöß:
Data Validation Utilizing Expert Knowledge and Shape Constraints. ACM J. Data Inf. Qual. 16(2): 13:1-13:27 (2024) - [j11]Daniel Parra, David Joedicke, J. Manuel Velasco, Gabriel Kronberger, José Ignacio Hidalgo:
Learning Difference Equations With Structured Grammatical Evolution for Postprandial Glycaemia Prediction. IEEE J. Biomed. Health Informatics 28(5): 3067-3078 (2024) - [c73]Patrick E. Leser, Geoffrey F. Bomarito, Gabriel Kronberger, Fabrício Olivetti de França:
Comparing Methods for Estimating Marginal Likelihood in Symbolic Regression. GECCO Companion 2024: 2058-2066 - [c72]Gabriel Kronberger, Fabrício Olivetti de França, Harry Desmond, Deaglan J. Bartlett, Lukas Kammerer:
The Inefficiency of Genetic Programming for Symbolic Regression. PPSN (1) 2024: 273-289 - [i30]Gabriel Kronberger, Fabrício Olivetti de França, Harry Desmond, Deaglan J. Bartlett, Lukas Kammerer:
The Inefficiency of Genetic Programming for Symbolic Regression - Extended Version. CoRR abs/2404.17292 (2024) - [i29]Yousef A. Radwan, Gabriel Kronberger, Stephan M. Winkler:
A Comparison of Recent Algorithms for Symbolic Regression to Genetic Programming. CoRR abs/2406.03585 (2024) - 2023
- [j10]Christian Haider, Fabrício Olivetti de França, Bogdan Burlacu, Gabriel Kronberger:
Shape-constrained multi-objective genetic programming for symbolic regression. Appl. Soft Comput. 132: 109855 (2023) - [c71]Fabrício Olivetti de França, Gabriel Kronberger:
Reducing Overparameterization of Symbolic Regression Models with Equality Saturation. GECCO 2023: 1064-1072 - [c70]Christian Haider, Fabrício Olivetti de França, Bogdan Burlacu, Florian Bachinger, Gabriel Kronberger, Michael Affenzeller:
Shape-constrained Symbolic Regression: Real-World Applications in Magnetization, Extrusion and Data Validation. GPTP 2023: 225-240 - [c69]Hannah Janout, Thomas Paier, Carina Ringelhahn, Michael Heckmann, Andreas Haghofer, Gabriel Kronberger, Stephan Winkler:
Identification of Surrogate Models for the Prediction of Degrees of Freedom within a Tolerance Chain. ISM 2023: 796-805 - [i28]Daniel Parra, David Joedicke, J. Manuel Velasco, Gabriel Kronberger, José Ignacio Hidalgo:
Learning Difference Equations with Structured Grammatical Evolution for Postprandial Glycaemia Prediction. CoRR abs/2307.01238 (2023) - [i27]Deaglan J. Bartlett, Lukas Kammerer, Gabriel Kronberger, Harry Desmond, Pedro G. Ferreira, Benjamin D. Wandelt, Bogdan Burlacu, David Alonso, Matteo Zennaro:
A precise symbolic emulator of the linear matter power spectrum. CoRR abs/2311.15865 (2023) - 2022
- [j9]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): 75-98 (2022) - [c68]Lukas Kammerer, Gabriel Kronberger, Michael Kommenda:
Symbolic Regression with Fast Function Extraction and Nonlinear Least Squares Optimization. EUROCAST 2022: 139-146 - [c67]Florian Bachinger, Gabriel Kronberger:
Comparing Shape-Constrained Regression Algorithms for Data Validation. EUROCAST 2022: 147-154 - [c66]Christian Haider, Gabriel Kronberger:
Shape-Constrained Symbolic Regression with NSGA-III. EUROCAST 2022: 164-172 - [c65]David Joedicke, Daniel Parra, Gabriel Kronberger, Stephan M. Winkler:
Identifying Differential Equations for the Prediction of Blood Glucose using Sparse Identification of Nonlinear Systems. EUROCAST 2022: 181-188 - [c64]Christian Haider, Fabrício Olivetti de França, Gabriel Kronberger, Bogdan Burlacu:
Comparing optimistic and pessimistic constraint evaluation in shape-constrained symbolic regression. GECCO 2022: 938-945 - [c63]Bogdan Burlacu, Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler, Michael Affenzeller:
Symbolic Regression in Materials Science: Discovering Interatomic Potentials from Data. GPTP 2022: 1-30 - [c62]Martin Steiger, Hans Georg Brachtendorf, Gabriel Kronberger:
Identification of Discrete Non-Linear Dynamics of a Radio-Frequency Power Amplifier Circuit using Symbolic Regression. SYNASC 2022: 297-303 - [c61]Gabriel Kronberger:
Local Optimization Often is Ill-conditioned in Genetic Programming for Symbolic Regression. SYNASC 2022: 304-310 - [c60]David Piringer, Bernhard Bloder, Gabriel Kronberger:
Steel Phase Kinetics Modeling using Symbolic Regression. SYNASC 2022: 327-330 - [i26]Bogdan Burlacu, Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler, Michael Affenzeller:
Symbolic Regression in Materials Science: Discovering Interatomic Potentials from Data. CoRR abs/2206.06422 (2022) - [i25]Gabriel Kronberger:
Local Optimization Often is Ill-conditioned in Genetic Programming for Symbolic Regression. CoRR abs/2209.00942 (2022) - [i24]Fabrício Olivetti de França, Gabriel Kronberger:
Prediction Intervals and Confidence Regions for Symbolic Regression Models based on Likelihood Profiles. CoRR abs/2209.06454 (2022) - [i23]Florian Bachinger, Gabriel Kronberger:
Comparing Shape-Constrained Regression Algorithms for Data Validation. CoRR abs/2209.09602 (2022) - [i22]Lukas Kammerer, Gabriel Kronberger, Michael Kommenda:
Symbolic Regression with Fast Function Extraction and Nonlinear Least Squares Optimization. CoRR abs/2209.09675 (2022) - [i21]David Jödicke, Daniel Parra, Gabriel Kronberger, Stephan M. Winkler:
Identifying Differential Equations to predict Blood Glucose using Sparse Identification of Nonlinear Systems. CoRR abs/2209.13852 (2022) - [i20]David Piringer, Bernhard Bloder, Gabriel Kronberger:
Steel Phase Kinetics Modeling using Symbolic Regression. CoRR abs/2212.10284 (2022) - 2021
- [c59]Laura Millán, Gabriel Kronberger, José Ignacio Hidalgo, Ricardo Fernández, Oscar Garnica, Gaspar González-Doncel:
Estimation of Grain-Level Residual Stresses in a Quenched Cylindrical Sample of Aluminum Alloy AA5083 Using Genetic Programming. EvoApplications 2021: 421-436 - [c58]Lukas Kammerer, Gabriel Kronberger, Stephan M. Winkler:
Empirical analysis of variance for genetic programming based symbolic regression. GECCO Companion 2021: 251-252 - [i19]Gabriel Kronberger, Fabrício Olivetti de França, Bogdan Burlacu, Christian Haider, Michael Kommenda:
Shape-constrained Symbolic Regression - Improving Extrapolation with Prior Knowledge. CoRR abs/2103.15624 (2021) - [i18]Gabriel Kronberger, Lukas Kammerer, Michael Kommenda:
Identification of Dynamical Systems using Symbolic Regression. CoRR abs/2107.06131 (2021) - [i17]Christian Haider, Fabrício Olivetti de França, Bogdan Burlacu, Gabriel Kronberger:
Using Shape Constraints for Improving Symbolic Regression Models. CoRR abs/2107.09458 (2021) - [i16]Gabriel Kronberger, Michael Kommenda, Andreas Promberger, Falk Nickel:
Predicting Friction System Performance with Symbolic Regression and Genetic Programming with Factor Variables. CoRR abs/2107.09484 (2021) - [i15]Bogdan Burlacu, Lukas Kammerer, Michael Affenzeller, Gabriel Kronberger:
Hash-Based Tree Similarity and Simplification in Genetic Programming for Symbolic Regression. CoRR abs/2107.10640 (2021) - [i14]Florian Bachinger, Gabriel Kronberger:
Concept for a Technical Infrastructure for Management of Predictive Models in Industrial Applications. CoRR abs/2107.13821 (2021) - [i13]Gabriel Kronberger, Evgeniya Kabliman, Johannes Kronsteiner, Michael Kommenda:
Predicting Calibration Parameter Values for Constitutive Models using Genetic Programming. CoRR abs/2108.01595 (2021) - [i12]Jan Zenisek, Gabriel Kronberger, Josef Wolfartsberger, Norbert Wild, Michael Affenzeller:
Concept Drift Detection with Variable Interaction Networks. CoRR abs/2108.03273 (2021) - [i11]Erik Pitzer, Gabriel Kronberger:
Smooth Symbolic Regression: Transformation of Symbolic Regression into a Real-valued Optimization Problem. CoRR abs/2108.03274 (2021) - [i10]Lukas Kammerer, Gabriel Kronberger, Michael Kommenda:
Data Aggregation for Reducing Training Data in Symbolic Regression. CoRR abs/2108.10660 (2021) - [i9]Michael Kommenda, Andreas Beham, Michael Affenzeller, Gabriel Kronberger:
Complexity Measures for Multi-objective Symbolic Regression. CoRR abs/2109.00238 (2021) - [i8]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 abs/2109.13895 (2021) - [i7]Gabriel Kronberger, Lukas Kammerer, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller:
Cluster Analysis of a Symbolic Regression Search Space. CoRR abs/2109.13898 (2021) - [i6]Michael Kommenda, Johannes Karder, Andreas Beham, Bogdan Burlacu, Gabriel Kronberger, Stefan Wagner, Michael Affenzeller:
Optimization Networks for Integrated Machine Learning. CoRR abs/2110.00415 (2021) - 2020
- [j8]Michael Kommenda, Bogdan Burlacu, Gabriel Kronberger, Michael Affenzeller:
Parameter identification for symbolic regression using nonlinear least squares. Genet. Program. Evolvable Mach. 21(3): 471-501 (2020) - [j7]Gabriel Kronberger, J. Manuel Colmenar, Stephan M. Winkler, José Ignacio Hidalgo:
Multilayer analysis of population diversity in grammatical evolution for symbolic regression. Soft Comput. 24(15): 11283-11295 (2020) - [c57]David Joedicke, Gabriel Kronberger, José Manuel Colmenar, Stephan M. Winkler, José Manuel Velasco, Sergio Contador, José Ignacio Hidalgo:
Analysis of the performance of Genetic Programming on the Blood Glucose Level Prediction Challenge 2020. KDH@ECAI 2020: 141-145 - [c56]Bogdan Burlacu, Gabriel Kronberger, Michael Kommenda:
Operon C++: an efficient genetic programming framework for symbolic regression. GECCO Companion 2020: 1562-1570
2010 – 2019
- 2019
- [c55]Stefan Prieschl, Dominic Girardi, Gabriel Kronberger:
Using Ontologies to Express Prior Knowledge for Genetic Programming. CD-MAKE 2019: 362-376 - [c54]Bogdan Burlacu, Michael Affenzeller, Gabriel Kronberger, Michael Kommenda:
Online Diversity Control in Symbolic Regression via a Fast Hash-based Tree Similarity Measure. CEC 2019: 2175-2182 - [c53]Florian Bachinger, Gabriel Kronberger:
Concept for a Technical Infrastructure for Management of Predictive Models in Industrial Applications. EUROCAST (1) 2019: 263-270 - [c52]Jan Zenisek, Gabriel Kronberger, Josef Wolfartsberger, Norbert Wild, Michael Affenzeller:
Concept Drift Detection with Variable Interaction Networks. EUROCAST (1) 2019: 296-303 - [c51]Bogdan Burlacu, Lukas Kammerer, Michael Affenzeller, Gabriel Kronberger:
Hash-Based Tree Similarity and Simplification in Genetic Programming for Symbolic Regression. EUROCAST (1) 2019: 361-369 - [c50]Gabriel Kronberger, Lukas Kammerer, Michael Kommenda:
Identification of Dynamical Systems Using Symbolic Regression. EUROCAST (1) 2019: 370-377 - [c49]Lukas Kammerer, Gabriel Kronberger, Michael Kommenda:
Data Aggregation for Reducing Training Data in Symbolic Regression. EUROCAST (1) 2019: 378-386 - [c48]Bogdan Burlacu, Gabriel Kronberger, Michael Kommenda, Michael Affenzeller:
Parsimony measures in multi-objective genetic programming for symbolic regression. GECCO (Companion) 2019: 338-339 - [c47]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: 79-99 - [i5]Bogdan Burlacu, Michael Affenzeller, Gabriel Kronberger, Michael Kommenda:
Online Diversity Control in Symbolic Regression via a Fast Hash-based Tree Similarity Measure. CoRR abs/1902.00882 (2019) - 2018
- [j6]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: 610-624 (2018) - [c46]Gabriel Kronberger, Michael Kommenda, Andreas Promberger, Falk Nickel:
Predicting friction system performance with symbolic regression and genetic programming with factor variables. GECCO 2018: 1278-1285 - [c45]Gabriel Kronberger, Lukas Kammerer, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller:
Cluster Analysis of a Symbolic Regression Search Space. GPTP 2018: 85-102 - [p6]José Ignacio Hidalgo, J. Manuel Colmenar, J. Manuel Velasco, Gabriel Kronberger, Stephan M. Winkler, Oscar Garnica, Juan Lanchares:
Identification of Models for Glucose Blood Values in Diabetics by Grammatical Evolution. Handbook of Grammatical Evolution 2018: 367-393 - 2017
- [j5]José Ignacio Hidalgo, J. Manuel Colmenar, Gabriel Kronberger, Stephan M. Winkler, Oscar Garnica, Juan Lanchares:
Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods. J. Medical Syst. 41(9): 142 (2017) - [c44]Gabriel Kronberger, Bogdan Burlacu, Michael Kommenda, Stephan M. Winkler, Michael Affenzeller:
Measures for the Evaluation and Comparison of Graphical Model Structures. EUROCAST (1) 2017: 283-290 - [c43]Michael Kommenda, Johannes Karder, Andreas Beham, Bogdan Burlacu, Gabriel Kronberger, Stefan Wagner, Michael Affenzeller:
Optimization Networks for Integrated Machine Learning. EUROCAST (1) 2017: 392-399 - [c42]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: 424-431 - [c41]Bogdan Burlacu, Michael Affenzeller, Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler:
Analysis of Schema Frequencies in Genetic Programming. EUROCAST (1) 2017: 432-438 - [c40]José Ignacio Hidalgo, J. Manuel Colmenar, Gabriel Kronberger, Stephan M. Winkler:
Glucose Prognosis by Grammatical Evolution. EUROCAST (1) 2017: 455-463 - [c39]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: 1553-1558 - [c38]Bogdan Burlacu, Michael Affenzeller, Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler:
Schema Analysis in Tree-Based Genetic Programming. GPTP 2017: 17-37 - 2016
- [j4]Stephan M. Winkler, Bonifacio Castaño, Sergio Luengo-Sanchez, Susanne Schaller, Gabriel Kronberger, Michael Affenzeller:
Heterogeneous model ensembles for short-term prediction of stock market trends. Int. J. Simul. Process. Model. 11(6): 504-513 (2016) - [c37]J. Manuel Colmenar, Stephan M. Winkler, Gabriel Kronberger, Esther Maqueda, Marta Botella, José Ignacio Hidalgo:
Predicting Glycemia in Diabetic Patients By Evolutionary Computation and Continuous Glucose Monitoring. GECCO (Companion) 2016: 1393-1400 - [c36]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: 1-17 - [c35]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: 51-63 - 2015
- [c34]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: 326-333 - [c33]Erik Pitzer, Gabriel Kronberger:
Smooth Symbolic Regression: Transformation of Symbolic Regression into a Real-Valued Optimization Problem. EUROCAST 2015: 375-383 - [c32]Michael Kommenda, Andreas Beham, Michael Affenzeller, Gabriel Kronberger:
Complexity Measures for Multi-objective Symbolic Regression. EUROCAST 2015: 409-416 - [c31]Gabriel Kronberger, Michael Kommenda, Stephan M. Winkler, Michael Affenzeller:
Using Contextual Information in Sequential Search for Grammatical Optimization Problems. EUROCAST 2015: 417-424 - [c30]Michael Kommenda, Gabriel Kronberger, Michael Affenzeller, Stephan M. Winkler, Bogdan Burlacu:
Evolving Simple Symbolic Regression Models by Multi-Objective Genetic Programming. GPTP 2015: 1-19 - [p5]Bogdan Burlacu, Michael Affenzeller, Stephan M. Winkler, Michael Kommenda, Gabriel Kronberger:
Methods for Genealogy and Building Block Analysis in Genetic Programming. Computational Intelligence and Efficiency in Engineering Systems 2015: 61-74 - [p4]Michael Kommenda, Michael Affenzeller, Gabriel Kronberger, Bogdan Burlacu, Stephan M. Winkler:
Multi-Population Genetic Programming with Data Migration for Symbolic Regression. Computational Intelligence and Efficiency in Engineering Systems 2015: 75-87 - [p3]Gabriel Kronberger, Michael Kommenda:
Search Strategies for Grammatical Optimization Problems - Alternatives to Grammar-Guided Genetic Programming. Computational Intelligence and Efficiency in Engineering Systems 2015: 89-102 - [p2]Erik Pitzer, Gabriel Kronberger:
Concise Supply-Chain Simulation Optimization for Large Scale Logistic Networks. Computational Intelligence and Efficiency in Engineering Systems 2015: 429-442 - 2014
- [j3]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): 6454-6462 (2014) - [c29]Andreas Beham, Johannes Karder, Gabriel Kronberger, Stefan Wagner, Michael Kommenda, Andreas Scheibenpflug:
Scripting and framework integration in heuristic optimization environments. GECCO (Companion) 2014: 1109-1116 - [c28]Michael Kommenda, Michael Affenzeller, Bogdan Burlacu, Gabriel Kronberger, Stephan M. Winkler:
Genetic programming with data migration for symbolic regression. GECCO (Companion) 2014: 1361-1366 - [c27]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: 91-107 - 2013
- [j2]David Robert White, James McDermott, Mauro Castelli, Luca Manzoni, Brian W. Goldman, Gabriel Kronberger, Wojciech Jaskowski, Una-May O'Reilly, Sean Luke:
Better GP benchmarks: community survey results and proposals. Genet. Program. Evolvable Mach. 14(1): 3-29 (2013) - [j1]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): 29-41 (2013) - [c26]Gabriel Kronberger:
Declarative Modeling and Bayesian Inference of Dark Matter Halos. EUROCAST (1) 2013: 195-202 - [c25]Gabriel Kronberger, Michael Kommenda:
Evolution of Covariance Functions for Gaussian Process Regression Using Genetic Programming. EUROCAST (1) 2013: 308-315 - [c24]Michael Kommenda, Michael Affenzeller, Gabriel Kronberger, Stephan M. Winkler:
Nonlinear Least Squares Optimization of Constants in Symbolic Regression. EUROCAST (1) 2013: 420-427 - [c23]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: 1121-1128 - [c22]Gabriel Kronberger, Michael Kommenda, Stefan Wagner, Heinz Dobler:
GPDL: a framework-independent problem definition language for grammar-guided genetic programming. GECCO (Companion) 2013: 1333-1340 - [c21]Bogdan Burlacu, Michael Affenzeller, Michael Kommenda, Stephan M. Winkler, Gabriel Kronberger:
Visualization of genetic lineages and inheritance information in genetic programming. GECCO (Companion) 2013: 1351-1358 - [c20]Michael Affenzeller, Stephan M. Winkler, Gabriel Kronberger, Michael Kommenda, Bogdan Burlacu, Stefan Wagner:
Gaining Deeper Insights in Symbolic Regression. GPTP 2013: 175-190 - [i4]Gabriel Kronberger, Michael Kommenda:
Evolution of Covariance Functions for Gaussian Process Regression using Genetic Programming. CoRR abs/1305.3794 (2013) - [i3]Gabriel Kronberger, Stephan M. Winkler, Michael Affenzeller, Andreas Beham, Stefan Wagner:
On the Success Rate of Crossover Operators for Genetic Programming with Offspring Selection. CoRR abs/1309.5896 (2013) - [i2]Michael Kommenda, Gabriel Kronberger, Christoph Feilmayr, Michael Affenzeller:
Data Mining using Unguided Symbolic Regression on a Blast Furnace Dataset. CoRR abs/1309.5931 (2013) - 2012
- [c19]Mathieu d'Aquin, Gabriel Kronberger, Mari Carmen Suárez-Figueroa:
Combining Data Mining and Ontology Engineering to Enrich Ontologies and Linked Data. KNOW@LOD 2012: 19-24 - [c18]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: 101-108 - [c17]Stefan Wagner, Gabriel Kronberger:
Algorithm and experiment design with heuristic lab: an open source optimization environment for research and education. GECCO (Companion) 2012: 1287-1316 - [c16]Gabriel Kronberger, Stefan Wagner, Michael Kommenda, Andreas Beham, Andreas Scheibenpflug, Michael Affenzeller:
Knowledge Discovery through Symbolic Regression with HeuristicLab. ECML/PKDD (2) 2012: 824-827 - [i1]Gabriel Kronberger, Stefan Fink, Michael Kommenda, Michael Affenzeller:
Macro-Economic Time Series Modeling and Interaction Networks. CoRR abs/1212.2044 (2012) - 2011
- [c15]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: 264-271 - [c14]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: 335-342 - [c13]Christoph Neumüller, Stefan Wagner, Gabriel Kronberger, Michael Affenzeller:
Parameter Meta-optimization of Metaheuristic Optimization Algorithms. EUROCAST (1) 2011: 367-374 - [c12]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: 400-407 - [c11]Gabriel Kronberger, Michael Affenzeller:
Market Basket Analysis of Retail Data: Supervised Learning Approach. EUROCAST (1) 2011: 464-471 - [c10]Gabriel Kronberger, Stefan Fink, Michael Kommenda, Michael Affenzeller:
Macro-economic Time Series Modeling and Interaction Networks. EvoApplications (2) 2011: 101-110 - [c9]Michael Kommenda, Gabriel Kronberger, Christoph Feilmayr, Michael Affenzeller:
Data Mining Using Unguided Symbolic Regression on a Blast Furnace Dataset. EvoApplications (1) 2011: 274-283 - [c8]Gabriel Kronberger, Michael Kommenda, Michael Affenzeller:
Overfitting detection and adaptive covariant parsimony pressure for symbolic regression. GECCO (Companion) 2011: 631-638 - [c7]Stefan Wagner, Gabriel Kronberger:
Algorithm and experiment design with heuristiclab: an open source optimization environment for research and education. GECCO (Companion) 2011: 1411-1438
2000 – 2009
- 2009
- [c6]Stefan Wagner, Gabriel Kronberger, Andreas Beham, Stephan M. Winkler, Michael Affenzeller:
Model Driven Rapid Prototyping of Heuristic Optimization Algorithms. EUROCAST 2009: 729-736 - [c5]Gabriel Kronberger, Stephan M. Winkler, Michael Affenzeller, Andreas Beham, Stefan Wagner:
On the Success Rate of Crossover Operators for Genetic Programming with Offspring Selection. EUROCAST 2009: 793-800 - [c4]Monika Kofler, Stefan Wagner, Andreas Beham, Gabriel Kronberger, Michael Affenzeller:
Priority Rule Generation with a Genetic Algorithm to Minimize Sequence Dependent Setup Costs. EUROCAST 2009: 817-824 - [c3]Gabriel Kronberger, Stephan M. Winkler, Michael Affenzeller, Stefan Wagner:
On Crossover Success Rate in Genetic Programming with Offspring Selection. EuroGP 2009: 232-243 - [p1]Michael Affenzeller, Andreas Beham, Monika Kofler, Gabriel Kronberger, Stefan A. Wagner, Stephan M. Winkler:
Metaheuristic Optimization. Hagenberg Research 2009: 103-155 - 2007
- [c2]Stefan Wagner, Stephan M. Winkler, Erik Pitzer, Gabriel Kronberger, Andreas Beham, Roland Braune, Michael Affenzeller:
Benefits of Plugin-Based Heuristic Optimization Software Systems. EUROCAST 2007: 747-754 - [c1]Gabriel Kronberger, Roland Braune:
Bandit-Based Monte-Carlo Planning for the Single-Machine Total Weighted Tardiness Scheduling Problem. EUROCAST 2007: 837-844
Coauthor Index
aka: Stefan A. Wagner
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