Michael Affenzeller

ORCID

Publication Activity (10 Years)

Years Active: 2001-2023
Publications (10 Years): 107

Top Venues

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)
Johannes Karder, Bernhard Werth, Andreas Beham, Stefan Wagner, Michael Affenzeller
A Novel Benchmark Environment for Dynamic Factory Crane Scheduling. ISM (2023)
David Muhr, Michael Affenzeller, Josef Küng
A Probabilistic Transformation of Distance-Based Outliers. Mach. Learn. Knowl. Extr. 5 (3) (2023)
Philipp Fleck, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller
Vectorial Genetic Programming - Optimizing Segments for Feature Extraction. CoRR (2023)
Kaifeng Yang, Michael Affenzeller
Surrogate-assisted Multi-objective Optimization via Genetic Programming Based Symbolic Regression. EMO (2023)
David Muhr, Michael Affenzeller, Josef Küng
Implicit Directed Acyclic Graphs (DAGs) for Parallel Outlier/Anomaly Detection Ensembles. AIAI (2) (2023)
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)
Du Nguyen Duy, Michael Affenzeller, Ramin Nikzad-Langerodi
Towards Vertical Privacy-Preserving Symbolic Regression via Secure Multiparty Computation. GECCO Companion (2023)
David Muhr, Michael Affenzeller, Josef Küng
Probabilistic Distance-Based Outlier Detection. CoRR (2023)
Holger Gröning, Jan Zenisek, Norbert Wild, Aziz Huskic, Michael Affenzeller
Method of Process Optimization for LMD-Processes using Machine Learning Algorithms. ISM (2023)
Du Nguyen Duy, Michael Affenzeller, Ramin Nikzad-Langerodi
Towards Vertical Privacy-Preserving Symbolic Regression via Secure Multiparty Computation. CoRR (2023)
Kaifeng Yang, Sixuan Liu, Michael Affenzeller, Guozhi Dong
Gradients of Acquisition Functions for Bi-objective Bayesian optimization. ICNC-FSKD (2023)
Kaifeng Yang, Kai Chen, Michael Affenzeller, Bernhard Werth
A New Acquisition Function for Multi-objective Bayesian Optimization: Correlated Probability of Improvement. GECCO Companion (2023)
Hao Wang, Kaifeng Yang, Michael Affenzeller, Michael Emmerich
Probability Distribution of Hypervolume Improvement in Bi-objective Bayesian Optimization. CoRR (2022)
David Piringer, Stefan Wagner, Christian Haider, Armin Fohler, Siegfried Silber, Michael Affenzeller
Improving the Flexibility of Shape-Constrained Symbolic Regression with Extended Constraints. EUROCAST (2022)
Jan Zenisek, Sebastian Dorl, Dominik Falkner, Lukas Gaisberger, Stephan M. Winkler, Michael Affenzeller
Shapley Value Based Variable Interaction Networks for Data Stream Analysis. EUROCAST (2022)
Kaifeng Yang, Guozhi Dong, Michael Affenzeller
A Parallel Technique for Multi-objective Bayesian Global Optimization: Using a Batch Selection of Probability of Improvement. CoRR (2022)
Vladimir Stanovov, Shakhnaz Akhmedova, Alexey Vakhnin, Evgenii Sopov, Eugene Semenkin, Michael Affenzeller
Improving the Quantum Multi-Swarm Optimization with Adaptive Differential Evolution for Dynamic Environments. Algorithms 15 (5) (2022)
Bernhard Werth, Erik Pitzer, Johannes Karder, Stefan Wagner, Michael Affenzeller
Dynamic Vehicle Routing with Time-Linkage: From Problem States to Algorithm Performance. 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)
Johannes Karder, Bernhard Werth, Andreas Beham, Stefan Wagner, Michael Affenzeller
Analysis and Handling of Dynamic Problem Changes in Open-Ended Optimization. EUROCAST (2022)
Kaifeng Yang, Michael Affenzeller, Guozhi Dong
A parallel technique for multi-objective Bayesian global optimization: Using a batch selection of probability of improvement. Swarm Evol. Comput. 75 (2022)
Michael Affenzeller, Michael Bögl, Lukas Fischer, Florian Sobieczky, Kaifeng Yang, Jan Zenisek
Prescriptive Analytics: When Data- and Simulation-based Models Interact in a Cooperative Way. SYNASC (2022)
Bogdan Burlacu, Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler, Michael Affenzeller
Symbolic Regression in Materials Science: Discovering Interatomic Potentials from Data. GPTP (2022)
David Muhr, Michael Affenzeller
Hybrid (CPU/GPU) Exact Nearest Neighbors Search in High-Dimensional Spaces. AIAI (2) (2022)
David Muhr, Michael Affenzeller, Anthony D. Blaom
OutlierDetection.jl: A modular outlier detection ecosystem for the Julia programming language. CoRR (2022)
David Muhr, Michael Affenzeller
Outlier/Anomaly Detection of Univariate Time Series: A Dataset Collection and Benchmark. DaWaK (2022)
Erik Pitzer, Michael Affenzeller
Cheating Like The Neighbors: Logarithmic Complexity For Fitness Evaluation In Genetic Algorithms. CEC (2021)
Kaifeng Yang, Michael Affenzeller
Quantifying Uncertainties of Residuals in Symbolic Regression via Kriging. ISM (2021)
Jan Zenisek, Holger Gröning, Norbert Wild, Aziz Huskic, Michael Affenzeller
Machine Learning based Data Stream Merging in Additive Manufacturing. ISM (2021)
Bernhard Werth, Andreas Beham, Johannes Karder, Stefan Wagner, Michael Affenzeller
Fitness Landscape Analysis on Binary Dynamic Optimization Problems. ISM (2021)
Philipp Fleck, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller
Grammar-Based Vectorial Genetic Programming for Symbolic Regression. GPTP (2021)
Kathrin Kefer, Roland Hanghofer, Patrick Kefer, Markus Stöger, Bernd Hofer, Michael Affenzeller, Stephan M. Winkler
Multi tree operators for genetic programming to identify optimal energy flow controllers. GECCO Companion (2021)
Bogdan Burlacu, Michael Affenzeller, Michael Kommenda
On the Effectiveness of Genetic Operations in Symbolic Regression. CoRR (2021)
Johannes Karder, Andreas Beham, Bernhard Werth, Stefan Wagner, Michael Affenzeller
Integrated Machine Learning in Open-Ended Crane Scheduling: Learning Movement Speeds and Service Times. ISM (2021)
Jan Zenisek, Gabriel Kronberger, Josef Wolfartsberger, Norbert Wild, Michael Affenzeller
Concept Drift Detection with Variable Interaction Networks. 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)
Michael Kommenda, Johannes Karder, Andreas Beham, Bogdan Burlacu, Gabriel Kronberger, Stefan Wagner, Michael Affenzeller
Optimization Networks for Integrated Machine Learning. CoRR (2021)
Bogdan Burlacu, Lukas Kammerer, Michael Affenzeller, Gabriel Kronberger
Hash-Based Tree Similarity and Simplification in Genetic Programming for Symbolic Regression. 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)
Johannes Karder, Andreas Beham, Viktoria A. Hauder, Klaus Altendorfer, Michael Affenzeller
Simulation-based optimisation for worker cross-training. Int. J. Simul. Process. Model. 16 (3) (2021)
David Muhr, Michael Affenzeller
Little data is often enough for distance-based outlier detection. ISM (2021)
Viktoria A. Hauder, Andreas Beham, Stefan Wagner, Karl F. Doerner, Michael Affenzeller
Dynamic online optimization in the context of smart manufacturing: an overview. ISM (2020)
Viktoria A. Hauder, Andreas Beham, Sebastian Raggl, Sophie N. Parragh, Michael Affenzeller
Resource-constrained multi-project scheduling with activity and time flexibility. Comput. Ind. Eng. 150 (2020)
Michael Kommenda, Bogdan Burlacu, Gabriel Kronberger, Michael Affenzeller
Parameter identification for symbolic regression using nonlinear least squares. Genet. Program. Evolvable Mach. 21 (3) (2020)
Oliver Krauss, Hanspeter Mössenböck, Michael Affenzeller
Towards Knowledge-guided Genetic Improvement. ICSE (Workshops) (2020)
Sebastian Raggl, Andreas Beham, Stefan Wagner, Michael Affenzeller
Solution approaches for the dynamic stacking problem. 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)
Jan Zenisek, Gabriel Kronberger, Josef Wolfartsberger, Norbert Wild, Michael Affenzeller
Concept Drift Detection with Variable Interaction Networks. EUROCAST (1) (2019)
Viktoria A. Hauder, Andreas Beham, Sebastian Raggl, Sophie N. Parragh, Michael Affenzeller
On constraint programming for a new flexible project scheduling problem with resource constraints. CoRR (2019)
Erik Pitzer, Michael Affenzeller
"Incremental" Evaluation for Genetic Crossover. EUROCAST (1) (2019)
Andreas Beham, Sebastian Raggl, Stefan Wagner, Michael Affenzeller
Uncertainty in real-world steel stacking problems. GECCO (Companion) (2019)
Bogdan Burlacu, Gabriel Kronberger, Michael Kommenda, Michael Affenzeller
Parsimony measures in multi-objective genetic programming for symbolic regression. GECCO (Companion) (2019)
Mariia Semenkina, Bogdan Burlacu, Michael Affenzeller
Genetic Programming Based Evolvement of Models of Models. EUROCAST (1) (2019)
Bernhard Werth, Erik Pitzer, Christian Backfrieder, Gerald Ostermayer, Michael Affenzeller
Surrogate-assisted microscopic traffic simulation-based optimisation of routing parameters. Int. J. Simul. Process. Model. 14 (3) (2019)
Bogdan Burlacu, Lukas Kammerer, Michael Affenzeller, Gabriel Kronberger
Hash-Based Tree Similarity and Simplification in Genetic Programming for Symbolic Regression. EUROCAST (1) (2019)
Sebastian Raggl, Andreas Beham, Michael Affenzeller
Investigating the Dynamic Block Relocation Problem. 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)
Jan Zenisek, Florian Holzinger, Michael Affenzeller
Machine learning based concept drift detection for predictive maintenance. Comput. Ind. Eng. 137 (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)
Viktoria A. Hauder, Andreas Beham, Sebastian Raggl, Michael Affenzeller
Solving a Flexible Resource-Constrained Project Scheduling Problem Under Consideration of Activity Priorities. EUROCAST (1) (2019)
Judith Fechter, Andreas Beham, Stefan Wagner, Michael Affenzeller
Approximate Q-Learning for Stacking Problems with Continuous Production and Retrieval. Appl. Artif. Intell. 33 (1) (2019)
Bernhard Werth, Erik Pitzer, Michael Affenzeller
Surrogate-Assisted Fitness Landscape Analysis for Computationally Expensive Optimization. EUROCAST (1) (2019)
Kathrin Kefer, Roland Hanghofer, Patrick Kefer, Markus Stöger, Michael Affenzeller, Stephan M. Winkler, Stefan Wagner, Bernd Hofer
A Model-Based Learning Approach for Controlling the Energy Flows of a Residential Household Using Genetic Programming to Perform Symbolic Regression. EUROCAST (1) (2019)
Oliver Krauss, Hanspeter Mössenböck, Michael Affenzeller
Mining patterns from genetic improvement experiments. GI@ICSE (2019)
Andreas Beham, Stefan Wagner, Michael Affenzeller
Algorithm selection on generalized quadratic assignment problem landscapes. GECCO (2018)
Lukas Kammerer, Michael Affenzeller
Confidence-based ensemble modeling in medical data mining. GECCO (Companion) (2018)
Sebastian Raggl, Andreas Beham, Viktoria A. Hauder, Stefan Wagner, Michael Affenzeller
Discrete real-world problems in a black-box optimization benchmark. GECCO (Companion) (2018)
Wojciech Bozejko, Andrzej Gnatowski, Teodor Nizynski, Michael Affenzeller, Andreas Beham
Local Optima Networks in Solving Algorithm Selection Problem for TSP. DepCoS-RELCOMEX (2018)
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)
Johannes Karder, Andreas Beham, Bernhard Werth, Stefan Wagner, Michael Affenzeller
Asynchronous surrogate-assisted optimization networks. GECCO (Companion) (2018)
Oliver Krauss, Hanspeter Mössenböck, Michael Affenzeller
Dynamic fitness functions for genetic improvement in compilers and interpreters. GECCO (Companion) (2018)
Bernhard Werth, Erik Pitzer, Gerald Ostermayer, Michael Affenzeller
Quasi-bistability of walk-based landscape measures in stochastic fitness landscapes. GECCO (2018)
Philipp Fleck, Michael Kommenda, Thorsten Prante, Michael Affenzeller
Novel robustness measures for engineering design optimisation. Int. J. Simul. Process. Model. 13 (4) (2018)
Jan Zenisek, Josef Wolfartsberger, Christoph Sievi, Michael Affenzeller
Modeling Sensor Networks for Predictive Maintenance. OTM Workshops (2018)
Bogdan Burlacu, Michael Affenzeller
Schema-based diversification in genetic programming. 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)
Erik Pitzer, Michael Affenzeller
Facilitating Evolutionary Algorithm Analysis with Persistent Data Structures. EUROCAST (1) (2017)
Bernhard Werth, Erik Pitzer, Michael Affenzeller
Enabling high-dimensional surrogate-assisted optimization by using sliding windows. 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)
Viktoria A. Hauder, Johannes Karder, Andreas Beham, Stefan Wagner, Michael Affenzeller
A General Solution Approach for the Location Routing Problem. EUROCAST (1) (2017)
Jan Zenisek, Michael Affenzeller, Josef Wolfartsberger, Mathias Silmbroth, Christoph Sievi, Aziz Huskic, Herbert Jodlbauer
Sliding Window Symbolic Regression for Predictive Maintenance Using Model Ensembles. EUROCAST (1) (2017)
Bernhard Werth, Erik Pitzer, Michael Affenzeller
A Fair Performance Comparison of Different Surrogate Optimization Strategies. EUROCAST (1) (2017)
Bogdan Burlacu, Michael Affenzeller, Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler
Schema Analysis in Tree-Based Genetic Programming. GPTP (2017)
Viktoria A. Hauder, Andreas Beham, Stefan Wagner, Michael Affenzeller
Optimization networks for real-world production and logistics problems. GECCO (Companion) (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)
Stefan Wagner, Andreas Beham, Michael Affenzeller
Analysis and Visualization of the Impact of Different Parameter Configurations on the Behavior of Evolutionary Algorithms. EUROCAST (1) (2017)
Andreas Beham, Erik Pitzer, Stefan Wagner, Michael Affenzeller
Integrating Exploratory Landscape Analysis into Metaheuristic Algorithms. EUROCAST (1) (2017)
Johannes Karder, Andreas Scheibenpflug, Andreas Beham, Stefan Wagner, Michael Affenzeller
Extending Sim# for simulation-based optimisation of semi-automated machinery. Int. J. Simul. Process. Model. 12 (6) (2017)
Sebastian Raggl, Andreas Beham, Stefan Wagner, Michael Affenzeller
Analysing a Hybrid Model-Based Evolutionary Algorithm for a Hard Grouping Problem. EUROCAST (1) (2017)
Johannes Karder, Andreas Beham, Stefan Wagner, Michael Affenzeller
Solving the Traveling Thief Problem Using Orchestration in Optimization Networks. 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)
Andreas Beham, Michael Affenzeller, Stefan Wagner
Instance-based algorithm selection on quadratic assignment problem landscapes. GECCO (Companion) (2017)
Bogdan Burlacu, Michael Affenzeller, Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler
Analysis of Schema Frequencies in Genetic Programming. EUROCAST (1) (2017)
Viktoria A. Hauder, Erik Pitzer, Michael Affenzeller
Optimization Approaches for the Physical Internet. OTM Workshops (2017)
Michael Kommenda, Johannes Karder, Andreas Beham, Bogdan Burlacu, Gabriel Kronberger, Stefan Wagner, Michael Affenzeller
Optimization Networks for Integrated Machine Learning. EUROCAST (1) (2017)
Andreas Scheibenpflug, Johannes Karder, Susanne Schaller, Stefan Wagner, Michael Affenzeller
Evolutionary Procedural 2D Map Generation using Novelty Search. GECCO (Companion) (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Michael Affenzeller