Lukás Bajer

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 24

Top Topics

Gaussian Process

Top Venues

GECCO (Companion)

Publications

Marek Dedic, Lukás Bajer, Pavel Procházka, Martin Holena
Balancing performance and complexity with adaptive graph coarsening. Tiny Papers @ ICLR (2024)
Simon Mandlík, Tomás Pevný, Václav Smídl, Lukás Bajer
Malicious Internet Entity Detection Using Local Graph Inference. IEEE Trans. Inf. Forensics Secur. 19 (2024)
Stepan Dvorak, Pavel Procházka, Lukás Bajer
GNN-Based Malicious Network Entities Identification In Large-Scale Network Data. NOMS (2022)
Paul Prasse, Jan Brabec, Jan Kohout, Martin Kopp, Lukás Bajer, Tobias Scheffer
Learning Explainable Representations of Malware Behavior. ECML/PKDD (4) (2021)
Paul Prasse, Jan Brabec, Jan Kohout, Martin Kopp, Lukás Bajer, Tobias Scheffer
Learning Explainable Representations of Malware Behavior. CoRR (2021)
Marek Dedic, Tomás Pevný, Lukás Bajer, Martin Holena
Loss Functions for Clustering in Multi-instance Learning. ITAT (2020)
Lukás Bajer, Zbynek Pitra, Jakub Repický, Martin Holena
Gaussian process surrogate models for the CMA-ES. GECCO (Companion) (2019)
Lukás Bajer, Zbynek Pitra, Jakub Repický, Martin Holena
Gaussian Process Surrogate Models for the CMA Evolution Strategy. Evol. Comput. 27 (4) (2019)
Jakub Repický, Lukás Bajer, Zbynek Pitra, Martin Holena
Adaptive Generation-Based Evolution Control for Gaussian Process Surrogate Models. ITAT (2017)
Zbynek Pitra, Lukás Bajer, Jakub Repický, Martin Holena
Adaptive Doubly Trained Evolution Control for the Covariance Matrix Adaptation Evolution Strategy. ITAT (2017)
Zbynek Pitra, Lukás Bajer, Jakub Repický, Martin Holena
Ordinal versus metric gaussian process regression in surrogate modelling for CMA evolution strategy. GECCO (Companion) (2017)
Jakub Repický, Lukás Bajer, Zbynek Pitra, Martin Holena
Adaptive Generation-Based Evolution Control for Gaussian Process Surrogate Models. CoRR (2017)
Zbynek Pitra, Lukás Bajer, Jakub Repický, Martin Holena
Overview of surrogate-model versions of covariance matrix adaptation evolution strategy. GECCO (Companion) (2017)
Zbynek Pitra, Lukás Bajer, Jakub Repický, Martin Holena
Comparison of ordinal and metric gaussian process regression as surrogate models for CMA evolution strategy. GECCO (Companion) (2017)
Zbynek Pitra, Lukás Bajer, Martin Holena
Doubly Trained Evolution Control for the Surrogate CMA-ES. PPSN (2016)
Jakub Repický, Lukás Bajer, Martin Holena
Traditional Gaussian Process Surrogates in the BBOB Framework. ITAT (2016)
Nikita Orekhov, Lukás Bajer, Martin Holena
Testing Gaussian Process Surrogates on CEC'2013 Multi-Modal Benchmark. ITAT (2016)
Lukás Bajer, Martin Holena
Model Guided Sampling Optimization for Low-dimensional Problems. CoRR (2015)
Martin Holena, Lukás Bajer, Martin Scavnicky
Using Copulas in Data Mining Based on the Observational Calculus. IEEE Trans. Knowl. Data Eng. 27 (10) (2015)
Lukás Bajer, Martin Holena
Model Guided Sampling Optimization for Low-dimensional Problems. ICAART (2) (2015)
Lukás Bajer, Zbynek Pitra, Martin Holena
Investigation of Gaussian Processes and Random Forests as Surrogate Models for Evolutionary Black-Box Optimization. GECCO (Companion) (2015)
Zbynek Pitra, Lukás Bajer, Martin Holena
Comparing SVM, Gaussian Process and Random Forest Surrogate Models for the CMA-ES. ITAT (2015)
Lukás Bajer, Zbynek Pitra, Martin Holena
Benchmarking Gaussian Processes and Random Forests Surrogate Models on the BBOB Noiseless Testbed. GECCO (Companion) (2015)
Andrej Kudinov, Lukás Bajer, Zbynek Pitra, Martin Holena
Investigation of Gaussian Processes in the Context of Black-Box Evolutionary Optimization. ITAT (2015)
Lukás Bajer, Martin Holena
Two Gaussian Approaches to Black-Box Optomization. CoRR (2014)
Lukás Bajer, Viktor Charypar, Martin Holena
Model guided sampling optimization with gaussian processes for expensive black-box optimization. GECCO (Companion) (2013)
Lukás Bajer, Martin Holena
Surrogate Model for Mixed-Variables Evolutionary Optimization Based on GLM and RBF Networks. SOFSEM (2013)
Lukás Bajer, Martin Holena
RBF-based surrogate model for evolutionary optimization. ITAT (2012)
Martin Holena, David Linke, Lukás Bajer
Surrogate modeling in the evolutionary optimization of catalytic materials. GECCO (2012)
Martin Holena, David Linke, Lukás Bajer
Case study: constraint handling in evolutionary optimization of catalytic materials. GECCO (Companion) (2011)
Lukás Bajer, Martin Holena
Surrogate Model for Continuous and Discrete Genetic Optimization Based on RBF Networks. IDEAL (2010)
Martin Holena, David Linke, Uwe Rodemerck, Lukás Bajer
Neural Networks as Surrogate Models for Measurements in Optimization Algorithms. ASMTA (2010)