Thresholding-a selection operator for noisy ES. - Sandor Markon; Dirk V. Arnold; Thomas Bäck; Thomas Beielstein; Hans-Georg Beyer (CEC, 2001)

Circuit design using evolutionary algorithms. - Thomas Beielstein; Jan Dienstuhl; Christian Feist; Marc Pompl (IEEE Congress on Evolutionary Computation, 2002)

Threshold selection, hypothesis tests, and DOE methods. - Thomas Beielstein; Sandor Markon (IEEE Congress on Evolutionary Computation, 2002)

Particle swarm optimizers for Pareto optimization with enhanced archiving techniques. - Thomas Bartz-Beielstein; Philipp Limbourg; Jörn Mehnen; Karlheinz Schmitt; Konstantinos E. Parsopoulos; Michael N. Vrahatis (IEEE Congress on Evolutionary Computation, 2003)

Optimal Elevator Group Control by Evolution Strategies. - Thomas Beielstein; Claus-Peter Ewald; Sandor Markon (GECCO, 2003)

Tuning search algorithms for real-world applications: a regression tree based approach. - Thomas Bartz-Beielstein; Sandor Markon (IEEE Congress on Evolutionary Computation, 2004)

Sequential parameter optimization. - Thomas Bartz-Beielstein; Christian Lasarczyk; Mike Preuss (Congress on Evolutionary Computation, 2005)

Evolution Strategies and Threshold Selection. - Thomas Bartz-Beielstein (Hybrid Metaheuristics, 2005)

New experimentalism applied to evolutionary computation. - Thomas Bartz-Beielstein (2005)

Experimental Research in Evolutionary Computation - The New Experimentalism. - Thomas Bartz-Beielstein (Springer, 2006)

The Impact of Group Reputation in Multiagent Environments. - Bastian Baranski; Thomas Bartz-Beielstein; Rüdiger Ehlers; Thusinthan Kajendran; Björn Kosslers; Jörn Mehnen; Tomasz Polaszek; Ralf Reimholz; Jens M. Schmidt; Karlheinz Schmitt; Danny Seis; Rafael Slodzinski; et al. (IEEE Congress on Evolutionary Computation, 2006)

Optimizing Door Assignment in LTL-Terminals by Evolutionary Multiobjective Algorithms. - Thomas Bartz-Beielstein; Annette Chmielewski; Michael Janas; Boris Naujoks; Robert Scheffermann (IEEE Congress on Evolutionary Computation, 2006)

High-order punishment and the evolution of cooperation. - Bastian Baranski; Thomas Bartz-Beielstein; Rüdiger Ehlers; Thusinthan Kajendran; Björn Kosslers; Jörn Mehnen; Tomasz Polaszek; Ralf Reimholz; Jens M. Schmidt; Karlheinz Schmitt; Danny Seis; Rafael Slodzinski; et al. (GECCO, 2006)

Investigation of One-Go Evolution Strategy/Quasi-Newton Hybridizations. - Thomas Bartz-Beielstein; Mike Preuss; Günter Rudolph (Hybrid Metaheuristics, 2006)

Particle Swarm Optimization and Sequential Sampling in Noisy Environments. - Thomas Bartz-Beielstein; Daniel Blum; Jürgen Branke (Metaheuristics, 2007)

Experimental research in evolutionary computation. - Thomas Bartz-Beielstein; Mike Preuss (GECCO (Companion), 2007)

Sequential Parameter Optimization Applied to Self-Adaptation for Binary-Coded Evolutionary Algorithms. - Mike Preuss; Thomas Bartz-Beielstein (Parameter Setting in Evolutionary Algorithms, 2007)

Reinforcement Learning: Insights from Interesting Failures in Parameter Selection. - Wolfgang Konen; Thomas Bartz-Beielstein (PPSN, 2008)

How experimental algorithmics can benefit from Mayo's extensions to Neyman-Pearson theory of testing. - Thomas Bartz-Beielstein (Synth., 2008)

Sequential Parameter Optimization. - Thomas Bartz-Beielstein (Sampling-based Optimization in the Presence of Uncertainty, 2009)

the future of experimental research. - Thomas Bartz-Beielstein; Mike Preuss (GECCO (Companion), 2009)

Reinforcement learning for games: failures and successes. - Wolfgang Konen; Thomas Bartz-Beielstein (GECCO (Companion), 2009)

Optimierte Modellierung von Füllständen in Regenüberlaufbecken mittels CI-basierter Parameterselektion (Optimized Modelling of Fill Levels in Stormwater Tanks Using CI-based Parameter Selection Schemes). - Wolfgang Konen; Tobias Zimmer; Thomas Bartz-Beielstein (Autom., 2009)

Introduction. - Thomas Bartz-Beielstein; Marco Chiarandini; Luís Paquete; Mike Preuss (Experimental Methods for the Analysis of Optimization Algorithms, 2010)

The Sequential Parameter Optimization Toolbox. - Thomas Bartz-Beielstein; Christian Lasarczyk; Mike Preuss (Experimental Methods for the Analysis of Optimization Algorithms, 2010)

The Future of Experimental Research. - Thomas Bartz-Beielstein; Mike Preuss (Experimental Methods for the Analysis of Optimization Algorithms, 2010)

Sequential Model-Based Parameter Optimization: an Experimental Investigation of Automated and Interactive Approaches. - Frank Hutter; Thomas Bartz-Beielstein; Holger H. Hoos; Kevin Leyton-Brown; Kevin P. Murphy (Experimental Methods for the Analysis of Optimization Algorithms, 2010)

Comparing SPO-tuned GP and NARX prediction models for stormwater tank fill level prediction. - Oliver Flasch; Thomas Bartz-Beielstein; Artur Davtyan; Patrick Koch; Wolfgang Konen; Tosin Daniel Oyetoyan; Michael Tamutan (IEEE Congress on Evolutionary Computation, 2010)

Optimization of biogas production with computational intelligence a comparative study. - Jörg Ziegenhirt; Thomas Bartz-Beielstein; Oliver Flasch; Wolfgang Konen; Martin Zaefferer (IEEE Congress on Evolutionary Computation, 2010)

Tuning and experimental analysis in evolutionary computation: what we still have wrong. - Thomas Bartz-Beielstein; Mike Preuss (GECCO (Companion), 2010)

RGP: an open source genetic programming system for the R environment. - Oliver Flasch; Olaf Mersmann; Thomas Bartz-Beielstein (GECCO (Companion), 2010)

SPOT: An R Package For Automatic and Interactive Tuning of Optimization Algorithms by Sequential Parameter Optimization - Thomas Bartz-Beielstein (CoRR, 2010)

Noisy optimization with sequential parameter optimization and optimal computational budget allocation. - Thomas Bartz-Beielstein; Martina Friese; Martin Zaefferer; Boris Naujoks; Oliver Flasch; Wolfgang Konen; Patrick Koch (GECCO (Companion), 2011)

Automatic and interactive tuning of algorithms. - Thomas Bartz-Beielstein; Mike Preuss (GECCO (Companion), 2011)

Tuned data mining: a benchmark study on different tuners. - Wolfgang Konen; Patrick Koch; Oliver Flasch; Thomas Bartz-Beielstein; Martina Friese; Boris Naujoks (GECCO, 2011)

SPOT applied to non-stochastic optimization problems: an experimental study. - Thomas Bartz-Beielstein; Martina Friese; Boris Naujoks; Martin Zaefferer (GECCO (Companion), 2012)

Sequential parameter optimization for symbolic regression. - Thomas Bartz-Beielstein; Oliver Flasch; Martin Zaefferer (GECCO (Companion), 2012)

Statistical analysis of optimization algorithms with R. - Thomas Bartz-Beielstein; Mike Preuß; Martin Zaefferer (GECCO (Companion), 2012)

Multi-criteria optimization for hard problems under limited budgets. - Martin Zaefferer; Thomas Bartz-Beielstein; Martina Friese; Boris Naujoks; Oliver Flasch (GECCO (Companion), 2012)

Editorial for the Special Issue on Automated Design and Assessment of Heuristic Search Methods. - Gabriela Ochoa; Mike Preuss; Thomas Bartz-Beielstein; Marc Schoenauer (Evol. Comput., 2012)

Tuning and evolution of support vector kernels. - Patrick Koch; Bernd Bischl; Oliver Flasch; Thomas Bartz-Beielstein; Claus Weihs; Wolfgang Konen (Evol. Intell., 2012)

A Case Study on Multi-Criteria Optimization of an Event Detection Software under Limited Budgets. - Martin Zaefferer; Thomas Bartz-Beielstein; Boris Naujoks; Tobias Wagner 001; Michael Emmerich 001 (EMO, 2013)

Comparing Ensemble-Based Forecasting Methods for Smart-Metering Data. - Oliver Flasch; Martina Friese; Katya Vladislavleva; Thomas Bartz-Beielstein; Olaf Mersmann; Boris Naujoks; Jörg Stork; Martin Zaefferer (EvoApplications, 2013)

How to create meaningful and generalizable results. - Thomas Bartz-Beielstein; Martin Zaefferer; Boris Naujoks (GECCO (Companion), 2013)

Tuning multi-objective optimization algorithms for cyclone dust separators. - Martin Zaefferer; Beate Breiderhoff; Boris Naujoks; Martina Friese; Jörg Stork; Andreas Fischbach; Oliver Flasch; Thomas Bartz-Beielstein (GECCO, 2014)

Efficient global optimization for combinatorial problems. - Martin Zaefferer; Jörg Stork; Martina Friese; Andreas Fischbach; Boris Naujoks; Thomas Bartz-Beielstein (GECCO, 2014)

Distance Measures for Permutations in Combinatorial Efficient Global Optimization. - Martin Zaefferer; Jörg Stork; Thomas Bartz-Beielstein (PPSN, 2014)

Evolutionary Algorithms. - Thomas Bartz-Beielstein; Jürgen Branke; Jörn Mehnen; Olaf Mersmann (WIREs Data Mining Knowl. Discov., 2014)

Experimental Analysis of Optimization Algorithms: Tuning and Beyond. - Thomas Bartz-Beielstein; Mike Preuss (Theory and Principled Methods for the Design of Metaheuristics, 2014)

Comparison of different Methods for Univariate Time Series Imputation in R. - Steffen Moritz; Alexis Sardá; Thomas Bartz-Beielstein; Martin Zaefferer; Jörg Stork (CoRR, 2015)

How to Create Generalizable Results. - Thomas Bartz-Beielstein (Handbook of Computational Intelligence, 2015)

Tutorials at PPSN 2016. - Carola Doerr; Nicolas Bredèche; Enrique Alba 001; Thomas Bartz-Beielstein; Dimo Brockhoff; Benjamin Doerr; Gusz Eiben; Michael G. Epitropakis; Carlos M. Fonseca; Andreia P. Guerreiro; Evert Haasdijk; Jacqueline Heinerman; et al. (PPSN, 2016)

Efficient Global Optimization with Indefinite Kernels. - Martin Zaefferer; Thomas Bartz-Beielstein (PPSN, 2016)

Multi-fidelity modeling and optimization of biogas plants. - Martin Zaefferer; Daniel Gaida; Thomas Bartz-Beielstein (Appl. Soft Comput., 2016)

Can social learning increase learning speed, performance or both? - Jacqueline Heinerman; Jörg Stork; Margarita Alejandra Rebolledo Coy; Julien Hubert; Thomas Bartz-Beielstein; A. E. Eiben; Evert Haasdijk (ECAL, 2017)

Is social learning more than parameter tuning? - Jacqueline Heinerman; Jörg Stork; Margarita Alejandra Rebolledo Coy; Julien Hubert; A. E. Eiben; Thomas Bartz-Beielstein; Evert Haasdijk (GECCO (Companion), 2017)

Simulation-based test functions for optimization algorithms. - Martin Zaefferer; Andreas Fischbach; Boris Naujoks; Thomas Bartz-Beielstein (GECCO, 2017)

Model-based methods for continuous and discrete global optimization. - Thomas Bartz-Beielstein; Martin Zaefferer (Appl. Soft Comput., 2017)

In a Nutshell: Sequential Parameter Optimization. - Thomas Bartz-Beielstein; Lorenzo Gentile; Martin Zaefferer (CoRR, 2017)

Conditional inference trees for knowledge extraction from motor health condition data. - Alexis Sardá; Subanatarajan Subbiah; Thomas Bartz-Beielstein (Eng. Appl. Artif. Intell., 2017)

imputeTS: Time Series Missing Value Imputation in R. - Steffen Moritz; Thomas Bartz-Beielstein (R J., 2017)

Surrogate assisted optimization of particle reinforced metal matrix composites. - Lorenzo Gentile; Martin Zaefferer; Dario Giugliano; Haofeng Chen; Thomas Bartz-Beielstein (GECCO, 2018)

Comparison of parallel surrogate-assisted optimization approaches. - Frederik Rehbach; Martin Zaefferer; Jörg Stork; Thomas Bartz-Beielstein (GECCO, 2018)

Linear Combination of Distance Measures for Surrogate Models in Genetic Programming. - Martin Zaefferer; Jörg Stork; Oliver Flasch; Thomas Bartz-Beielstein (PPSN (2), 2018)

Distance-based Kernels for Surrogate Model-based Neuroevolution. - Jörg Stork; Martin Zaefferer; Thomas Bartz-Beielstein (CoRR, 2018)

A new Taxonomy of Continuous Global Optimization Algorithms. - Jörg Stork; A. E. Eiben; Thomas Bartz-Beielstein (CoRR, 2018)

Bridging Theory and Practice Through Modular Graphical User Interfaces. - Frederik Rehbach; Jörg Stork; Thomas Bartz-Beielstein (J. Multim. Process. Technol., 2018)

Autonomous Generation of Observation Schedules for Tracking Satellites with Structured-Chromosome GA Optimisation. - Cristian Greco; Lorenzo Gentile; Gianluca Filippi; Edmondo A. Minisci; Massimiliano Vasile; Thomas Bartz-Beielstein (CEC, 2019)

Evaluation of Cognitive Architectures for Cyber-Physical Production Systems. - Andreas Bunte; Andreas Fischbach; Jan Strohschein; Thomas Bartz-Beielstein; Heide Faeskorn-Woyke; Oliver Niggemann (ETFA, 2019)

Improving NeuroEvolution Efficiency by Surrogate Model-Based Optimization with Phenotypic Distance Kernels. - Jörg Stork; Martin Zaefferer; Thomas Bartz-Beielstein (EvoApplications, 2019)

Structured-chromosome GA optimisation for satellite tracking. - Lorenzo Gentile; Cristian Greco; Edmondo A. Minisci; Thomas Bartz-Beielstein; Massimiliano Vasile (GECCO (Companion), 2019)

Feature selection for surrogate model-based optimization. - Frederik Rehbach; Lorenzo Gentile; Thomas Bartz-Beielstein (GECCO (Companion), 2019)

Surrogate models for enhancing the efficiency of neuroevolution in reinforcement learning. - Jörg Stork; Martin Zaefferer; Thomas Bartz-Beielstein; A. E. Eiben (GECCO, 2019)

Why we need an AI-resilient society. - Thomas Bartz-Beielstein (CoRR, 2019)

An empirical approach for probing the definiteness of kernels. - Martin Zaefferer; Thomas Bartz-Beielstein; Günter Rudolph (Soft Comput., 2019)

Hybrid Variable Selection and Support Vector Regression for Gas Sensor Optimization. - Margarita Rebolledo; Ruxandra Stoean; A. E. Eiben; Thomas Bartz-Beielstein (BIOMA, 2020)

Understanding the Behavior of Reinforcement Learning Agents. - Jörg Stork; Martin Zaefferer; Thomas Bartz-Beielstein; A. E. Eiben (BIOMA, 2020)

Preliminary spacecraft design by means of Structured-Chromosome Genetic Algorithms. - Lorenzo Gentile; Gianluca Filippi; Edmondo A. Minisci; Thomas Bartz-Beielstein; Massimiliano Vasile (CEC, 2020)

High-Lift Devices Topology Optimisation using Structured-Chromosome Genetic Algorithm. - Lorenzo Gentile; Elisa Morales; Domenico Quagliarella; Edmondo A. Minisci; Thomas Bartz-Beielstein; Renato Tognaccini (CEC, 2020)

Parallelized bayesian optimization for problems with expensive evaluation functions. - Margarita Alejandra Rebolledo Coy; Frederik Rehbach; A. E. Eiben; Thomas Bartz-Beielstein (GECCO Companion, 2020)

Variable reduction for surrogate-based optimization. - Frederik Rehbach; Lorenzo Gentile; Thomas Bartz-Beielstein (GECCO, 2020)

Expected improvement versus predicted value in surrogate-based optimization. - Frederik Rehbach; Martin Zaefferer; Boris Naujoks; Thomas Bartz-Beielstein (GECCO, 2020)

Parallelized Bayesian Optimization for Expensive Robot Controller Evolution. - Margarita Alejandra Rebolledo Coy; Frederik Rehbach; A. E. Eiben; Thomas Bartz-Beielstein (PPSN (1), 2020)

Improving the reliability of test functions generators. - Andreas Fischbach; Thomas Bartz-Beielstein (Appl. Soft Comput., 2020)

CAAI - A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems. - Andreas Fischbach; Jan Strohschein; Andreas Bunte; Jörg Stork; Heide Faeskorn-Woyke; Natalia Moriz; Thomas Bartz-Beielstein (CoRR, 2020)

Benchmarking in Optimization: Best Practice and Open Issues. - Thomas Bartz-Beielstein; Carola Doerr; Jakob Bossek; Sowmya Chandrasekaran; Tome Eftimov; Andreas Fischbach; Pascal Kerschke; Manuel López-Ibáñez 001; Katherine M. Malan; Jason H. Moore; Boris Naujoks; Patryk Orzechowski; et al. (CoRR, 2020)

Simulation of an Elevator Group Control Using Generative Adversarial Networks and Related AI Tools. - Tom Peetz; Sebastian Vogt; Martin Zaefferer; Thomas Bartz-Beielstein (CoRR, 2020)

Optimization of High-dimensional Simulation Models Using Synthetic Data. - Thomas Bartz-Beielstein; Eva Bartz; Frederik Rehbach; Olaf Mersmann (CoRR, 2020)

Sensor Placement for Contamination Detection in Water Distribution Systems. - Margarita Alejandra Rebolledo Coy; Sowmya Chandrasekaran; Thomas Bartz-Beielstein (CoRR, 2020)

EventDetectR - An Open-Source Event Detection System. - Sowmya Chandrasekaran; Margarita Rebolledo; Thomas Bartz-Beielstein (CoRR, 2020)

Cognitive Capabilities for the CAAI in Cyber-Physical Production Systems. - Jan Strohschein; Andreas Fischbach; Andreas Bunte; Heide Faeskorn-Woyke; Natalia Moriz; Thomas Bartz-Beielstein (CoRR, 2020)

Hospital Capacity Planning Using Discrete Event Simulation Under Special Consideration of the COVID-19 Pandemic. - Thomas Bartz-Beielstein; Frederik Rehbach; Olaf Mersmann; Eva Bartz (CoRR, 2020)

Technical Report: Flushing Strategies in Drinking Water Systems. - Margarita Rebolledo; Sowmya Chandrasekaran; Thomas Bartz-Beielstein (CoRR, 2020)

Open Issues in Surrogate-Assisted Optimization. - Jörg Stork; Martina Friese; Martin Zaefferer; Thomas Bartz-Beielstein; Andreas Fischbach; Beate Breiderhoff; Boris Naujoks; Tea Tusar (High-Performance Simulation-Based Optimization, 2020)

Optimization and Adaptation of a Resource Planning Tool for Hospitals Under Special Consideration of the COVID-19 Pandemic. - Thomas Bartz-Beielstein; Marcel Dröscher; Alpar Gür; Alexander Hinterleitner; Tom Lawton; Olaf Mersmann; Dessislava Peeva; Lennard Reese; Nicolas Rehbach; Frederik Rehbach; Amrita Sen; Aleksandr Subbotin; et al. (CEC, 2021)

Bayesian Networks for Mood Prediction Using Unobtrusive Ecological Momentary Assessments. - Margarita Rebolledo; A. E. Eiben; Thomas Bartz-Beielstein (EvoApplications, 2021)

Resource planning for hospitals under special consideration of the COVID-19 pandemic: optimization and sensitivity analysis. - Thomas Bartz-Beielstein; Marcel Dröscher; Alpar Gür; Alexander Hinterleitner; Olaf Mersmann; Dessislava Peeva; Lennard Reese; Nicolas Rehbach; Frederik Rehbach; A. Sen; Aleksandr Subbotin; Martin Zaefferer (GECCO Companion, 2021)

Impact of energy efficiency on the morphology and behaviour of evolved robots. - Margarita Rebolledo; Daan Zeeuwe; Thomas Bartz-Beielstein; A. E. Eiben (GECCO Companion, 2021)

Behavior-based neuroevolutionary training in reinforcement learning. - Jörg Stork; Martin Zaefferer; Nils Eisler; Patrick Tichelmann; Thomas Bartz-Beielstein; A. E. Eiben (GECCO Companion, 2021)

Resource Planning for Hospitals Under Special Consideration of the COVID-19 Pandemic: Optimization and Sensitivity Analysis. - Thomas Bartz-Beielstein; Marcel Dröscher; Alpar Gür; Alexander Hinterleitner; Olaf Mersmann; Dessislava Peeva; Lennard Reese; Nicolas Rehbach; Frederik Rehbach; Amrita Sen; Aleksandr Subbotin; Martin Zaefferer (CoRR, 2021)

Surrogate Model Based Hyperparameter Tuning for Deep Learning with SPOT. - Thomas Bartz-Beielstein (CoRR, 2021)

Experimental Investigation and Evaluation of Model-based Hyperparameter Optimization. - Eva Bartz; Martin Zaefferer; Olaf Mersmann; Thomas Bartz-Beielstein (CoRR, 2021)

Underwater Acoustic Networks for Security Risk Assessment in Public Drinking Water Reservoirs. - Jörg Stork; Philip Wenzel; Severin Landwein; María-Elena Algorri; Martin Zaefferer; Wolfgang Kusch; Martin Staubach; Thomas Bartz-Beielstein; Hartmut Köhn; Hermann Dejager; Christian Wolf 003 (CoRR, 2021)

Elevator group control as a constrained multiobjective optimization problem. - Aljosa Vodopija; Jörg Stork; Thomas Bartz-Beielstein; Bogdan Filipic (Appl. Soft Comput., 2022)

Co-optimizing for task performance and energy efficiency in evolvable robots. - Margarita Rebolledo; Daan Zeeuwe; Thomas Bartz-Beielstein; A. E. Eiben (Eng. Appl. Artif. Intell., 2022)

A new taxonomy of global optimization algorithms. - Jörg Stork; A. E. Eiben; Thomas Bartz-Beielstein (Nat. Comput., 2022)

Benchmark-Driven Configuration of a Parallel Model-Based Optimization Algorithm. - Frederik Rehbach; Martin Zaefferer; Andreas Fischbach; Günter Rudolph; Thomas Bartz-Beielstein (IEEE Trans. Evol. Comput., 2022)

Hyperparameter Tuning and Optimization Applications. - Thomas Bartz-Beielstein (Hyperparameter Tuning for Machine and Deep Learning with R, 2023)

Case Study II: Tuning of Gradient Boosting (xgboost). - Thomas Bartz-Beielstein; Sowmya Chandrasekaran; Frederik Rehbach (Hyperparameter Tuning for Machine and Deep Learning with R, 2023)

Case Study III: Tuning of Deep Neural Networks. - Thomas Bartz-Beielstein; Sowmya Chandrasekaran; Frederik Rehbach (Hyperparameter Tuning for Machine and Deep Learning with R, 2023)

Case Study I: Tuning Random Forest (Ranger). - Thomas Bartz-Beielstein; Sowmya Chandrasekaran; Frederik Rehbach; Martin Zaefferer (Hyperparameter Tuning for Machine and Deep Learning with R, 2023)

Ranking and Result Aggregation. - Thomas Bartz-Beielstein; Olaf Mersmann; Sowmya Chandrasekaran (Hyperparameter Tuning for Machine and Deep Learning with R, 2023)

Models. - Thomas Bartz-Beielstein; Martin Zaefferer (Hyperparameter Tuning for Machine and Deep Learning with R, 2023)

Hyperparameter Tuning Approaches. - Thomas Bartz-Beielstein; Martin Zaefferer (Hyperparameter Tuning for Machine and Deep Learning with R, 2023)

Tuning: Methodology. - Thomas Bartz-Beielstein; Martin Zaefferer; Olaf Mersmann (Hyperparameter Tuning for Machine and Deep Learning with R, 2023)

Global Study: Influence of Tuning. - Martin Zaefferer; Olaf Mersmann; Thomas Bartz-Beielstein (Hyperparameter Tuning for Machine and Deep Learning with R, 2023)

A Robust Statistical Framework for the Analysis of the Performances of Stochastic Optimization Algorithms Using the Principles of Severity. - Sowmya Chandrasekaran; Thomas Bartz-Beielstein (EvoApplications@EvoStar, 2023)

PyTorch Hyperparameter Tuning - A Tutorial for spotPython. - Thomas Bartz-Beielstein (CoRR, 2023)

Hyperparameter Tuning Cookbook: A guide for scikit-learn, PyTorch, river, and spotPython. - Thomas Bartz-Beielstein (CoRR, 2023)

Simplifying Hyperparameter Tuning in Online Machine Learning - The spotRiverGUI. - Thomas Bartz-Beielstein (CoRR, 2024)

A Novel Ranking Scheme for the Performance Analysis of Stochastic Optimization Algorithms using the Principles of Severity. - Sowmya Chandrasekaran; Thomas Bartz-Beielstein (CoRR, 2024)

Enhancing Feature Selection and Interpretability in AI Regression Tasks Through Feature Attribution. - Alexander Hinterleitner; Thomas Bartz-Beielstein; Richard Schulz; Sebastian Spengler; Thomas Winter; Christoph Leitenmeier (CoRR, 2024)

Bed-Attached Vibration Sensor System: A Machine Learning Approach for Fall Detection in Nursing Homes. - Thomas Bartz-Beielstein; Axel Wellendorf; Noah Pütz; Jens Brandt; Alexander Hinterleitner; Richard Schulz; Richard Scholz; Olaf Mersmann; Robin Knabe (CoRR, 2024)

Multi-Objective Optimization and Hyperparameter Tuning With Desirability Functions. - Thomas Bartz-Beielstein (CoRR, 2025)

Tuning for Trustworthiness - Balancing Performance and Explanation Consistency in Neural Network Optimization. - Alexander Hinterleitner; Thomas Bartz-Beielstein (CoRR, 2025)