Combining multiobjective and single-objective genetic algorithms in heterogeneous island model. - Martin Pilát; Roman Neruda (IEEE Congress on Evolutionary Computation, 2010)

ASM-MOMA: Multiobjective memetic algorithm with aggregate surrogate model. - Martin Pilát; Roman Neruda (IEEE Congress on Evolutionary Computation, 2011)

LAMM-MMA: multiobjective memetic algorithm with local aggregate meta-model. - Martin Pilát; Roman Neruda (GECCO (Companion), 2011)

Improving many-objective optimizers with aggregate meta-models. - Martin Pilát; Roman Neruda (HIS, 2011)

Meta Learning in Multi-agent Systems for Data Mining. - Ondrej Kazík; Klára Pesková; Martin Pilát; Roman Neruda (IAT, 2011)

Local Meta-models for ASM-MOMA. - Martin Pilát; Roman Neruda (ICIC (3), 2011)

Implementation of Parameter Space Search for Meta Learning in a Data-Mining Multi-agent System. - Ondrej Kazík; Klára Pesková; Martin Pilát; Roman Neruda (ICMLA (2), 2011)

An evolutionary algorithm for 2D semi-guillotinable circular saw cutting. - Stepán Balcar; Martin Pilát; Roman Neruda (IEEE Congress on Evolutionary Computation, 2012)

An Evolutionary Strategy for Surrogate-Based Multiobjective Optimization. - Martin Pilát; Roman Neruda (IEEE Congress on Evolutionary Computation, 2012)

A surrogate multiobjective evolutionary strategy with local search and pre-selection. - Martin Pilát; Roman Neruda (GECCO (Companion), 2012)

A Novel Meta Learning System and Its Application to Optimization of Computing Agents' Results. - Ondrej Kazík; Klára Pesková; Martin Pilát; Roman Neruda (IAT, 2012)

Combining Parameter Space Search and Meta-learning for Data-Dependent Computational Agent Recommendation. - Ondrej Kazík; Klára Pesková; Martin Pilát; Roman Neruda (ICMLA (2), 2012)

Meta-learning and Model Selection in Multi-objective Evolutionary Algorithms. - Martin Pilát; Roman Neruda (ICMLA (1), 2012)

A Surrogate Based Multiobjective Evolution Strategy with Different Models for Local Search and Pre-selection. - Martin Pilát; Roman Neruda (ICTAI, 2012)

Surrogate model selection for evolutionary multiobjective optimization. - Martin Pilát; Roman Neruda (IEEE Congress on Evolutionary Computation, 2013)

Multiobjectivization for classifier parameter tuning. - Martin Pilát; Roman Neruda (GECCO (Companion), 2013)

Multi-objectivization and Surrogate Modelling for Neural Network Hyper-parameters Tuning. - Martin Pilát; Roman Neruda (ICIC (3), 2013)

Aggregate meta-models for evolutionary multiobjective and many-objective optimization. - Martin Pilát; Roman Neruda (Neurocomputing, 2013)

The effect of different local search algorithms on the performance of multi-objective optimizers. - Martin Pilát; Roman Neruda (IEEE Congress on Evolutionary Computation, 2014)

Hybrid Multi-Agent System for Metalearning in Data Mining. - Klára Pesková; Jakub Smíd; Martin Pilát; Ondrej Kazík; Roman Neruda (MetaSel@ECAI, 2014)

Hypervolume-based local search in multi-objective evolutionary optimization. - Martin Pilát; Roman Neruda (GECCO, 2014)

Co-evolutionary genetic programming for dataset similarity induction. - Jakub Smíd; Martin Pilát; Klára Pesková; Roman Neruda (CEC, 2015)

Incorporating User Preferences in MOEA/D through the Coevolution of Weights. - Martin Pilát; Roman Neruda (GECCO, 2015)

Hypervolume-Based Surrogate Model for MO-CMA-ES. - Martin Pilát; Roman Neruda (ICTAI, 2015)

Generating Workflow Graphs Using Typed Genetic Programming. - Tomás Kren; Martin Pilát; Klára Pesková; Roman Neruda (MetaSel@PKDD/ECML, 2015)

Evolving Workflow Graphs Using Typed Genetic Programming. - Toma Ken; Martin Pilát; Roman Neruda (SSCI, 2015)

Multi-Objective Genetic Programming for Dataset Similarity Induction. - Jakub Smíd; Martin Pilát; Klára Pesková; Roman Neruda (SSCI, 2015)

General tuning of weights in MOEA/D. - Martin Pilát; Roman Neruda (CEC, 2016)

Asynchronous Evolution of Data Mining Workflow Schemes by Strongly Typed Genetic Programming. - Martin Pilát; Tomás Kren; Roman Neruda (ICTAI, 2016)

Feature Extraction for Surrogate Models in Genetic Programming. - Martin Pilát; Roman Neruda (PPSN, 2016)

Parallel evolutionary algorithm with interleaving generations. - Martin Pilát; Roman Neruda (GECCO, 2017)

Towards a Safer Planning and Execution Concept. - Lukás Chrpa; Jakub Gemrot; Martin Pilát (ICTAI, 2017)

Multi-objective evolution of machine learning workflows. - Tomás Kren; Martin Pilát; Roman Neruda (SSCI, 2017)

Unsupervised and Supervised Activity Analysis of Drone Sensor Data. - Roman Neruda; Martin Pilát; Josef Moudrík (WEA, 2017)

Automatic Creation of Machine Learning Workflows with Strongly Typed Genetic Programming. - Tomás Kren; Martin Pilát; Roman Neruda (Int. J. Artif. Intell. Tools, 2017)

Evolving Controllers for Electric Vehicle Charging. - Martin Pilát (EvoApplications, 2018)

Heterogeneous island model with re-planning of methods. - Stepán Balcar; Martin Pilát (GECCO (Companion), 2018)

Online Parallel Portfolio Selection with Heterogeneous Island Model. - Stepán Balcar; Martin Pilát (ICTAI, 2018)

Evolving Ensembles of Traffic Lights Controllers. - Martin Pilát (ICTAI, 2018)

Controlling the Charging of Electric Vehicles with Neural Networks. - Martin Pilát (IJCNN, 2018)

Compiling Planning Problems with Non-deterministic Events into FOND Planning. - Lukás Chrpa; Martin Pilát; Jakub Gemrot (RCRA/RiCeRcA@AI*IA, 2019)

Using Local Convolutional Units to Defend Against Adversarial Examples. - Matej Kocián; Martin Pilát (IJCNN, 2019)

Composing Multi-Instrumental Music with Recurrent Neural Networks. - David Samuel; Martin Pilát (IJCNN, 2019)

Planning and Acting with Non-Deterministic Events: Navigating between Safe States. - Lukás Chrpa; Jakub Gemrot; Martin Pilát (AAAI, 2020)

Heterogeneous Island Models and Their Application to Recommender Systems and Electric Vehicle Charging. - Stepán Balcar; Martin Pilát (Int. J. Artif. Intell. Tools, 2020)

Training Electric Vehicle Charging Controllers with Imitation Learning. - Martin Pilát (ICTAI, 2021)

Beating White-Box Defenses with Black-Box Attacks. - Vera Kumová; Martin Pilát (IJCNN, 2021)

On Eventual Applicability of Plans in Dynamic Environments with Cyclic Phenomena. - Lukás Chrpa; Martin Pilát; Jakub Med (KR, 2021)

Using graph neural networks as surrogate models in genetic programming. - Martin Pilát; Gabriela Suchopárová (GECCO Companion, 2022)

Implementing and evaluating parallel evolutionary algorithms in modern GPU computing libraries. - Patrik Valkovic; Martin Pilát (GECCO Companion, 2022)

Planning and acting in dynamic environments: identifying and avoiding dangerous situations. - Lukás Chrpa; Martin Pilát; Jakub Gemrot (J. Exp. Theor. Artif. Intell., 2022)

Improving Tiled Evolutionary Adversarial Attack. - Vera Cervícková; Martin Pilát (PKDD/ECML Workshops (2), 2023)

ProMap: Datasets for Product Mapping in E-commerce. - Katerina Macková; Martin Pilát (CoRR, 2023)

ProMap: Product Mapping Datasets. - Katerina Macková; Martin Pilát (ECIR (2), 2024)

Surprisingly Strong Performance Prediction with Neural Graph Features. - Gabriela Kadlecová; Jovita Lukasik; Martin Pilát; Petra Vidnerová; Mahmoud Safari; Roman Neruda; Frank Hutter (ICML, 2024)

Enhancing Multi-Agent Robustness: Addressing the Off-Diagonal Problem with Population-Based Training. - Petra Vysusilová; Premysl Basta; Martin Pilát (ICTAI, 2024)

Transferrable Surrogates in Expressive Neural Architecture Search Spaces. - Shiwen Qin; Gabriela Kadlecová; Martin Pilát; Shay B. Cohen; Roman Neruda; Elliot J. Crowley; Jovita Lukasik; Linus Ericsson (CoRR, 2025)