| 2025 | FedCSIS | Assigning scientific texts to existing ontologies. | Luks Korel, Martin Holena |
| 2025 | GECCO | Landscape Analysis for Surrogate Models in the Evolutionary Black-Box Context (Extended Abstract). | Zbynek Pitra, Jan Koza, Jir Tumpach, Martin Holena |
| 2024 | ICLR | Balancing performance and complexity with adaptive graph coarsening. | Marek Dedic, Luks Bajer, Pavel Prochzka, Martin Holena |
| 2024 | ICLR | On Difficulties of Attention Factorization through Shared Memory. | Uladzislau Yorsh, Martin Holena, Ondrej Bojar, David Herel |
| 2023 | IC3K | Using Paraphrasers to Detect Duplicities in Ontologies. | Luks Korel, Alexander S. Behr, Norbert Kockmann, Martin Holena |
| 2022 | ESANN | Neural-network-based estimation of normal distributions in black-box optimization. | Jir Tumpach, Jan Koza, Martin Holena |
| 2022 | IJCNN | On Combining Robustness and Regularization in Training Multilayer Perceptrons over Small Data. | Jan Kalina, Jir Tumpach, Martin Holena |
| 2021 | GECCO | Interaction between model and its evolution control in surrogate-assisted CMA evolution strategy. | Zbynek Pitra, Marek Hanus, Jan Koza, Jir Tumpach, Martin Holena |
| 2019 | GECCO | Gaussian process surrogate models for the CMA-ES. | Luks Bajer, Zbynek Pitra, Jakub Repick, Martin Holena |
| 2019 | GECCO | Landscape analysis of gaussian process surrogates for the covariance matrix adaptation evolution strategy. | Zbynek Pitra, Jakub Repick, Martin Holena |
| 2017 | GECCO | Ordinal versus metric gaussian process regression in surrogate modelling for CMA evolution strategy. | Zbynek Pitra, Luks Bajer, Jakub Repick, Martin Holena |
| 2017 | GECCO | Overview of surrogate-model versions of covariance matrix adaptation evolution strategy. | Zbynek Pitra, Luks Bajer, Jakub Repick, Martin Holena |
| 2017 | GECCO | Comparison of ordinal and metric gaussian process regression as surrogate models for CMA evolution strategy. | Zbynek Pitra, Luks Bajer, Jakub Repick, Martin Holena |
| 2016 | PPSN | Doubly Trained Evolution Control for the Surrogate CMA-ES. | Zbynek Pitra, Luks Bajer, Martin Holena |
| 2015 | GECCO | Benchmarking Gaussian Processes and Random Forests Surrogate Models on the BBOB Noiseless Testbed. | Luks Bajer, Zbynek Pitra, Martin Holena |
| 2015 | GECCO | Investigation of Gaussian Processes and Random Forests as Surrogate Models for Evolutionary Black-Box Optimization. | Luks Bajer, Zbynek Pitra, Martin Holena |
| 2015 | ICAART | Model Guided Sampling Optimization for Low-dimensional Problems. | Luks Bajer, Martin Holena |
| 2014 | PPSN | A Generalized Markov-Chain Modelling Approach to (1, λ)-ES Linear Optimization. | Alexandre Adrien Chotard, Martin Holena |
| 2013 | GECCO | Model guided sampling optimization with gaussian processes for expensive black-box optimization. | Luks Bajer, Viktor Charypar, Martin Holena |
| 2013 | SOFSEM | Surrogate Model for Mixed-Variables Evolutionary Optimization Based on GLM and RBF Networks. | Luks Bajer, Martin Holena |
| 2012 | GECCO | Surrogate modeling in the evolutionary optimization of catalytic materials. | Martin Holena, David Linke, Luks Bajer |
| 2011 | GECCO | Case study: constraint handling in evolutionary optimization of catalytic materials. | Martin Holena, David Linke, Luks Bajer |
| 2010 | IDEAL | Surrogate Model for Continuous and Discrete Genetic Optimization Based on RBF Networks. | Luks Bajer, Martin Holena |
| 2010 | ISDA | Dynamic classifier aggregation using fuzzy integral with interaction-sensitive fuzzy measure. | David Stefka, Martin Holena |
| 2009 | ICAART | Classifier Aggregation using Local Classification Confidence. | David Stefka, Martin Holena |
| 2009 | ICONIP | Boosted Neural Networks in Evolutionary Computation. | Martin Holena, David Linke, Norbert Steinfeldt |
| 2007 | ECSQARU | Measures of Ruleset Quality Capable to Represent Uncertain Validity. | Martin Holena |
| 2007 | ECSQARU | The Use of Fuzzy t-Conorm Integral for Combining Classifiers. | David Stefka, Martin Holena |
| 2002 | DIS | Extraction of Logical Rules from Data by Means of Piecewise-Linear Neural Networks. | Martin Holena |
| 1998 | DIS | Formal Logics of Discovery and Hypothesis Formation by Machine. | Petr Hjek, Martin Holena |
| 1994 | DEXA | Integrating Frames, Rules and Uncertainty in a Database-Coupled Knowledge-Representation System. | Petra Drescher, Martin Holena, Rainer Kruschinski, Gernod Laufktter |