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07/17/2023
Hyperparameter Tuning Cookbook: A guide for scikit-learn, PyTorch, river, and spotPython
This document provides a comprehensive guide to hyperparameter tuning us...
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05/19/2023
PyTorch Hyperparameter Tuning - A Tutorial for spotPython
The goal of hyperparameter tuning (or hyperparameter optimization) is to...
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07/29/2021
Underwater Acoustic Networks for Security Risk Assessment in Public Drinking Water Reservoirs
We have built a novel system for the surveillance of drinking water rese...
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07/19/2021
Experimental Investigation and Evaluation of Model-based Hyperparameter Optimization
Machine learning algorithms such as random forests or xgboost are gainin...
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07/12/2021
Impact of Energy Efficiency on the Morphology and Behaviour of Evolved Robots
Most evolutionary robotics studies focus on evolving some targeted behav...
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05/30/2021
Surrogate Model Based Hyperparameter Tuning for Deep Learning with SPOT
A surrogate model based hyperparameter tuning approach for deep learning...
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05/17/2021
Behavior-based Neuroevolutionary Training in Reinforcement Learning
In addition to their undisputed success in solving classical optimizatio...
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05/16/2021
Resource Planning for Hospitals Under Special Consideration of the COVID-19 Pandemic: Optimization and Sensitivity Analysis
Crises like the COVID-19 pandemic pose a serious challenge to health-car...
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12/25/2020
Technical Report: Flushing Strategies in Drinking Water Systems
Drinking water supply and distribution systems are critical infrastructu...
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12/14/2020
Hospital Capacity Planning Using Discrete Event Simulation Under Special Consideration of the COVID-19 Pandemic
We present a resource-planning tool for hospitals under special consider...
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12/03/2020
Cognitive Capabilities for the CAAI in Cyber-Physical Production Systems
This paper presents the cognitive module of the cognitive architecture f...
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11/16/2020
EventDetectR – An Open-Source Event Detection System
EventDetectR: An efficient Event Detection System (EDS) capable of detec...
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09/06/2020
Optimization of High-dimensional Simulation Models Using Synthetic Data
Simulation models are valuable tools for resource usage estimation and c...
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09/03/2020
Simulation of an Elevator Group Control Using Generative Adversarial Networks and Related AI Tools
Testing new, innovative technologies is a crucial task for safety and ac...
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07/07/2020
Benchmarking in Optimization: Best Practice and Open Issues
This survey compiles ideas and recommendations from more than a dozen re...
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02/26/2020
CAAI – A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems
This paper introduces CAAI, a novel cognitive architecture for artificia...
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01/09/2020
Expected Improvement versus Predicted Value in Surrogate-Based Optimization
Surrogate-based optimization relies on so-called infill criteria (acquis...
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12/18/2019
Why we need an AI-resilient society
Artificial intelligence is considered as a key technology. It has a huge...
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07/22/2019
Surrogate Models for Enhancing the Efficiency of Neuroevolution in Reinforcement Learning
In the last years, reinforcement learning received a lot of attention. O...
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02/22/2019
Evaluation of Cognitive Architectures for Cyber-Physical Production Systems
Cyber-physical production systems (CPPS) integrate physical and computat...
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02/09/2019
Improving NeuroEvolution Efficiency by Surrogate Model-based Optimization with Phenotypic Distance Kernels
In NeuroEvolution, the topologies of artificial neural networks are opti...
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08/27/2018
A new Taxonomy of Continuous Global Optimization Algorithms
Surrogate-based optimization and nature-inspired metaheuristics have bec...
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07/20/2018
Distance-based Kernels for Surrogate Model-based Neuroevolution
The topology optimization of artificial neural networks can be particula...
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07/10/2018
An Empirical Approach For Probing the Definiteness of Kernels
Models like support vector machines or Gaussian process regression often...
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07/03/2018
Linear Combination of Distance Measures for Surrogate Models in Genetic Programming
Surrogate models are a well established approach to reduce the number of...
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12/12/2017
In a Nutshell: Sequential Parameter Optimization
The performance of optimization algorithms relies crucially on their par...
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10/13/2015
Comparison of different Methods for Univariate Time Series Imputation in R
Missing values in datasets are a well-known problem and there are quite ...
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06/23/2010