Lukás Bajer - RankMe

35 papers A 2B 2C 1Journal 9Unranked 20

Year	Rank	Type	Title / Venue / Authors
2024	—	`conf`	Balancing performance and complexity with adaptive graph coarsening. Tiny Papers @ ICLR Marek Dedic, Lukás Bajer, Pavel Procházka, Martin Holena
2024	J	`jnl`	Convolutional Signal Propagation: A Simple Scalable Algorithm for Hypergraphs. CoRR Pavel Procházka, Marek Dedic, Lukás Bajer
2024	J	`jnl`	Malicious Internet Entity Detection Using Local Graph Inference. CoRR Simon Mandlík, Tomás Pevný, Václav Smídl, Lukás Bajer
2024	J	`jnl`	Malicious Internet Entity Detection Using Local Graph Inference. IEEE Trans. Inf. Forensics Secur. Simon Mandlík, Tomás Pevný, Václav Smídl, Lukás Bajer
2022	B	`conf`	GNN-Based Malicious Network Entities Identification In Large-Scale Network Data. NOMS Stepan Dvorak, Pavel Procházka, Lukás Bajer
2021	—	`conf`	Learning Explainable Representations of Malware Behavior. ECML/PKDD (4) Paul Prasse, Jan Brabec, Jan Kohout, Martin Kopp, Lukás Bajer, Tobias Scheffer
2021	J	`jnl`	Learning Explainable Representations of Malware Behavior. CoRR Paul Prasse, Jan Brabec, Jan Kohout, Martin Kopp, Lukás Bajer, Tobias Scheffer
2020	—	`conf`	Loss Functions for Clustering in Multi-instance Learning. ITAT Marek Dedic, Tomás Pevný, Lukás Bajer, Martin Holena
2019	J	`jnl`	Gaussian Process Surrogate Models for the CMA Evolution Strategy. Evol. Comput. Lukás Bajer, Zbynek Pitra, Jakub Repický, Martin Holena
2019	—	`conf`	Gaussian process surrogate models for the CMA-ES. GECCO (Companion) Lukás Bajer, Zbynek Pitra, Jakub Repický, Martin Holena
2017	—	`conf`	Adaptive Doubly Trained Evolution Control for the Covariance Matrix Adaptation Evolution Strategy. ITAT Zbynek Pitra, Lukás Bajer, Jakub Repický, Martin Holena
2017	—	`conf`	Adaptive Generation-Based Evolution Control for Gaussian Process Surrogate Models. ITAT Jakub Repický, Lukás Bajer, Zbynek Pitra, Martin Holena
2017	J	`jnl`	Adaptive Generation-Based Evolution Control for Gaussian Process Surrogate Models. CoRR Jakub Repický, Lukás Bajer, Zbynek Pitra, Martin Holena
2017	—	`conf`	Comparison of ordinal and metric gaussian process regression as surrogate models for CMA evolution strategy. GECCO (Companion) Zbynek Pitra, Lukás Bajer, Jakub Repický, Martin Holena
2017	—	`conf`	Ordinal versus metric gaussian process regression in surrogate modelling for CMA evolution strategy. GECCO (Companion) Zbynek Pitra, Lukás Bajer, Jakub Repický, Martin Holena
2017	—	`conf`	Overview of surrogate-model versions of covariance matrix adaptation evolution strategy. GECCO (Companion) Zbynek Pitra, Lukás Bajer, Jakub Repický, Martin Holena
2016	A	`conf`	Doubly Trained Evolution Control for the Surrogate CMA-ES. PPSN Zbynek Pitra, Lukás Bajer, Martin Holena
2016	—	`conf`	Testing Gaussian Process Surrogates on CEC'2013 Multi-Modal Benchmark. ITAT Nikita Orekhov, Lukás Bajer, Martin Holena
2016	—	`conf`	Traditional Gaussian Process Surrogates in the BBOB Framework. ITAT Jakub Repický, Lukás Bajer, Martin Holena
2015	—	`conf`	Benchmarking Gaussian Processes and Random Forests Surrogate Models on the BBOB Noiseless Testbed. GECCO (Companion) Lukás Bajer, Zbynek Pitra, Martin Holena
2015	—	`conf`	Comparing SVM, Gaussian Process and Random Forest Surrogate Models for the CMA-ES. ITAT Zbynek Pitra, Lukás Bajer, Martin Holena
2015	—	`conf`	Investigation of Gaussian Processes and Random Forests as Surrogate Models for Evolutionary Black-Box Optimization. GECCO (Companion) Lukás Bajer, Zbynek Pitra, Martin Holena
2015	—	`conf`	Investigation of Gaussian Processes in the Context of Black-Box Evolutionary Optimization. ITAT Andrej Kudinov, Lukás Bajer, Zbynek Pitra, Martin Holena
2015	—	`conf`	Model Guided Sampling Optimization for Low-dimensional Problems. ICAART (2) Lukás Bajer, Martin Holena
2015	J	`jnl`	Model Guided Sampling Optimization for Low-dimensional Problems. CoRR Lukás Bajer, Martin Holena
2015	J	`jnl`	Using Copulas in Data Mining Based on the Observational Calculus. IEEE Trans. Knowl. Data Eng. Martin Holena, Lukás Bajer, Martin Scavnicky
2014	—	`ed.`	Proceedings of the main track of the 14th Conference on Information Technologies - Applications and Theory (ITAT 2014), with selected papers from Znalosti 2014 collocated with Znalosti 2014, Demanovska Dolina - Jasna, Slovakia, September 25 - 29, 2014. ITAT Vera Kurková, Lukás Bajer, Vojtech Svátek
2014	J	`jnl`	Two Gaussian Approaches to Black-Box Optomization. CoRR Lukás Bajer, Martin Holena
2013	—	`conf`	Model guided sampling optimization with gaussian processes for expensive black-box optimization. GECCO (Companion) Lukás Bajer, Viktor Charypar, Martin Holena
2013	B	`conf`	Surrogate Model for Mixed-Variables Evolutionary Optimization Based on GLM and RBF Networks. SOFSEM Lukás Bajer, Martin Holena
2012	—	`conf`	RBF-based surrogate model for evolutionary optimization. ITAT Lukás Bajer, Martin Holena
2012	A	`conf`	Surrogate modeling in the evolutionary optimization of catalytic materials. GECCO Martin Holena, David Linke, Lukás Bajer
2011	—	`conf`	Case study: constraint handling in evolutionary optimization of catalytic materials. GECCO (Companion) Martin Holena, David Linke, Lukás Bajer
2010	—	`conf`	Neural Networks as Surrogate Models for Measurements in Optimization Algorithms. ASMTA Martin Holena, David Linke, Uwe Rodemerck, Lukás Bajer
2010	C	`conf`	Surrogate Model for Continuous and Discrete Genetic Optimization Based on RBF Networks. IDEAL Lukás Bajer, Martin Holena