Jan Zegklitz

14 papers Journal 10Unranked 4
YearRankTypeTitle / Venue / Authors
2021 J jnl
Benchmarking state-of-the-art symbolic regression algorithms.
Genet. Program. Evolvable Mach.
Jan Zegklitz, Petr Posík
2021 J jnl
Control of Magnetic Manipulator Using Reinforcement Learning Based on Incrementally Adapted Local Linear Models.
Complex.
Martin Brablc, Jan Zegklitz, Robert Grepl, Robert Babuska
2021 J jnl
Symbolic Regression Methods for Reinforcement Learning.
IEEE Access
Jirí Kubalík, Erik Derner, Jan Zegklitz, Robert Babuska
2019 — conf
Sequential Model Building in Symbolic Regression.
ITAT
Jan Zegklitz, Petr Posík
2019 J jnl
Symbolic Regression Methods for Reinforcement Learning.
CoRR
Jirí Kubalík, Jan Zegklitz, Erik Derner, Robert Babuska
2019 J jnl
Symbolic regression in dynamic scenarios with gradually changing targets.
Appl. Soft Comput.
Jan Zegklitz, Petr Posík
2017 J jnl
Learning Linear Feature Space Transformations in Symbolic Regression.
CoRR
Jan Zegklitz, Petr Posík
2017 — conf
Linear combinations of features as leaf nodes in symbolic regression.
GECCO (Companion)
Jan Zegklitz, Petr Posík
2017 J jnl
Symbolic Regression Algorithms with Built-in Linear Regression.
CoRR
Jan Zegklitz, Petr Posík
2016 J jnl
Hybrid Single Node Genetic Programming for Symbolic Regression.
Trans. Comput. Collect. Intell.
Jirí Kubalík, Eduard Alibekov, Jan Zegklitz, Robert Babuska
2015 J jnl
Innovative default prediction approach.
Expert Syst. Appl.
Július Bems, Oldrich Starý, Martin Macas, Jan Zegklitz, Petr Posík
2015 — conf
Model Selection and Overfitting in Genetic Programming: Empirical Study.
GECCO (Companion)
Jan Zegklitz, Petr Posík
2015 J jnl
Model Selection and Overfitting in Genetic Programming: Empirical Study.
CoRR
Jan Zegklitz, Petr Posík
2015 — conf
Symbolic Regression by Grammar-based Multi-Gene Genetic Programming.
GECCO (Companion)
Jan Zegklitz, Petr Posík